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Measurement Blind Spots · supplied 1 November 2026

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Supplied working research · no experiment performed.

Analytical derivations and simulations are source-reported, not independently reproduced during publication. No published dataset was directly reanalysed. Source readiness/novelty scores are author assessments, not validation or novelty clearance. Original claims, corrections and negative results are retained.

Measurement Blind Spots

300 hypotheses about what experimental science fails to see, 30 developed in detail, and three investigated with working mathematics.

Compiled 1 November 2026. Every entry is a proposition, not a report of a measurement. No experiment described in this collection has been performed.


What this is

Science advances by measuring. It also accumulates blind spots: quantities an instrument cannot observe, parameters that are fitted rather than measured, approximations that are exact in the regime where they were tested and wrong in the regime where they are used, and disagreements between two accepted methods that are resolved by convention rather than by evidence.

This collection is a systematic hunt for those blind spots. It contains:

The seven blind-spot classes

Every hypothesis is tagged with one:

Class Count What it means
boundary-condition 64 The measurement is dominated by an interface, edge, or finite-size term that the model omits
hidden-parameter 54 A quantity is fitted, assumed, or inherited from a protocol rather than measured
time-dependent 37 Drift, aging, relaxation, or protocol timing sets the result
model-disagreement 27 Two accepted methods give different answers and both are internally consistent
model-artifact 27 The analysis procedure manufactures the effect it reports
nonlinearity 17 A linear or small-signal approximation fails where it is used
selection 13 The sample is chosen in a way correlated with the effect
circularity 12 The calibration is defined by the quantity it measures
assumption 10 A standard approximation is applied outside its domain
blind-spot 8 The instrument is structurally incapable of observing the relevant quantity
degeneracy 6 Two parameters enter identically and cannot be separated
artefact 5 A known analysis artefact in a new place

Three good places to start

  1. I2 — the spot-size bias. A closed-form result showing that in one limit the reported in-plane thermal conductivity of a 2D material stops depending on the material and becomes a function of the substrate conductance and the laser spot size. The predicted signature (κ_app ∝ s²) is checkable against published data with no new experiment.

  2. I3 — Kramers–Kronig blindness. The spectrum at 100 mV is a Debye element to eight digits, so it passes every KK test, while the charge-transfer resistance it returns is 36% low. The standard validity test is provably incapable of seeing the dominant systematic.

  3. R04 — a negative result. The common explanation for OD600 growth-curve compression (stray light) is quantitatively insufficient below OD 1.5. The calculation is included, the hypothesis is narrowed rather than rescued, and the low-OD mechanism is left open.

How to read an entry

Each of the 300 has the same seven fields:

What this collection is not

It is not a review. Absence of an entry is not a judgement. Several entries are deliberately contrarian and are marked as such. The readiness scores are optimistic by design: a 4 means someone could test it soon, not that the test is easy. And no entry claims an observation that was not made.

Files

File What it is
Blind-Spots.pdf The full document, typeset for reading
Blind-Spots.docx The same text in Word
hyp/01-physics.md … hyp/06-crosscutting.md The 300, by domain, canonical Markdown
data/hypotheses_300.csv / .json The 300 as structured data, one row per hypothesis
refined/R01-R15.md, refined/R16-R30.md The 30 refined hypotheses
investigations/ Three investigations: code, data, figures, writeup
data/r1_refinement_numbers.json Every quantitative number quoted in the refined set
sources.csv Every external source cited, with a verified identifier
CORRECTIONS.md Corrections, negative results, and superseded claims
METHODOLOGY.md How the set was built, the scales, and the limits

Part I — Three investigations

Three hypotheses were developed with full mathematical and computational treatment. All three are model computations: no physical experiment was performed, no apparatus was built, and no measured data are reported as new. Where a result is an identity or a property of the analysis rather than a claim about nature, it is labelled as such in the writeups below and in refined/.

Every number quoted here is regenerated by the scripts in this directory from the stated equations, with fixed random seeds where randomness is involved.

Investigation Type Key result Script
I1 Finite-window decay exponents mathematical + Monte Carlo α_fit = α·⟨logistic⟩; exact factor 2 at the crossover; offset recoverable from curvature I1_offset_window_bias.py
I2 Spot-size bias in in-plane thermal conductivity analytic + numerical κ_app/κ = 1/[e^λE₁(λ)]; κ_app → Gs²/(2d) independent of the material I2_boundary_bias.py
I3 Kramers–Kronig blindness to amplitude harmonic balance + Bessel identity R_ct falls to 0.64 at 100 mV while the spectrum remains a Debye to 1e-7 I3_kk_blindspot.py

I1 — The exponent you report is a property of your window

Question. When a decay is reported as a power law, how much of the exponent is the system and how much is the fit window?

Model. y(t) = At^(−α) + c, with c an unsubtracted offset. This is the most common situation in practice: a baseline that was not measured, or was measured badly.

Exact result. With x = ln t and B = c/A, the local log–log slope is

s(x) = −α / (1 + B e^{αx}),

a logistic in ln t of width 1/α, centred at the crossover t_c = (A/c)^{1/α}. A straight-line fit returns the least-squares average of that logistic. In particular, a window centred on the crossover returns exactly α/2 — an identity, not an empirical finding.

Numerics. A 2D map of α_fit/α over window width R ∈ [0.5, 6] decades and window placement log₁₀(t_c/t_mid) ∈ [−4, 4] (figure figs/i1_biasmap.png, panel A) shows that the bias spans 0.02 to 1.6. Monte Carlo with 400 realisations per configuration at 2% noise confirms the map and shows that a three-parameter fit (ln A, α, B) recovers α with bias 1.000 ± 0.011 even where the two-parameter fit is 0.50.

Identifiability. The Cramér–Rao bound on α (panel B) diverges when the window lies below the crossover: if you only see the flat part, α is not determined at any precision. That is the hard limit behind the folklore that “a power law cannot be distinguished from an exponential decay”.

What is new here. The logistic slope law is an identity. What is not obvious, and is falsifiable, is that (i) the offset is identifiable from curvature, so the correction is possible rather than merely a caveat; (ii) the correction is exact for windows that span the crossover; and (iii) the bias is bounded below 1% for windows well below the crossover, so the artefact cannot be invoked to explain a literature-wide discrepancy without checking where the crossover lies.

What would refute it. Published exponents unchanged by a free offset, with zero curvature, at the stated noise.

I1
I1b

Files. I1_offset_window_bias.py, data/i1_bias_maps.npz, data/i1_mc.csv, data/i1_summary.json, figs/i1_biasmap.png, figs/i1_logistic.png.


I2 — A hidden substrate conductance sets every optical measurement of in-plane thermal conductivity

Question. Why do reported in-plane thermal conductivities of the same 2D material vary by factors of two to three between laboratories?

Model. A thin sheet of thickness d and conductivity κ on a substrate with interface conductance G, heated by a Gaussian spot of 1/e² radius s with absorbed power P. Steady state:

κd∇²T − GT = −q(r), q(r) = (P/2πs²)e^(−r²/2s²).

A Hankel transform gives, at the beam centre,

ΔT = (P/4πκd)·e^λE₁(λ), λ = Gs²/(2κd).

Exact result. The standard analysis assumes λ → 0 and therefore reports

κ_app = κ / [e^λE₁(λ)].

This crosses unity at λ = 1, so the bias changes sign within a typical experimental campaign (the crossover spot radius is s* = √(2κd/G) = 0.58 µm for κ = 50 W m⁻¹K⁻¹, d = 100 nm, G = 3×10⁷ W m⁻²K⁻¹).

Validation. The closed form agrees with direct numerical Hankel quadrature to 2×10⁻¹³ across λ from 10⁻³ to 10.

The sharp limit. For λ ≫ 1, κ_app → Gs²/(2d): the reported conductivity stops depending on the material and becomes a function of the substrate conductance and the beam size. Over plausible (s, G) ranges the model produces a 136-fold spread in reported κ for one true value.

Identifiability. A single spot size gives one number and cannot determine both κ and G (the Fisher matrix is rank-deficient; Cramér–Rao diverges). Two spot sizes in a 1:3 ratio give σ(κ)/κ = 0.037 at 1% noise; three spanning 1:10 give 0.022. More laser powers do not help.

Testable prediction. Reanalysed κ values from a published compilation should collapse onto a single true κ when plotted against λ computed from each study’s spot radius and substrate conductance, and should scale as s² at large s. A slope of 2 on log κ_app vs log s is the falsifiable signature.

Limits. The model is isotropic, steady-state, optically thin, and treats the substrate as a single conductance. Anisotropy, finite substrate thickness, and the transducer boundary add unmodelled terms; the 136-fold figure is an upper bound for the stated parameter range, not a prediction for any named material.

I2
I2b

Files. I2_boundary_bias.py, data/i2_R_of_lambda.csv, data/i2_collapse.csv, data/i2_summary.json, figs/i2_bias.png, figs/i2_spread.png.


I3 — A Kramers–Kronig-consistent spectrum is not evidence of linearity

Question. Impedance spectra are screened with a Kramers–Kronig residual and accepted when it is small. Does passing that test mean the spectrum is linear?

Model. A Butler–Volmer interface with transfer coefficients α_a = α_c = 0.5, exchange current i₀ = 1 µA, double-layer capacitance 20 µF, series resistance 10 Ω. Drive V = V_dc + A sin ωt and solve the full harmonic balance: η(t) is expanded in 10 harmonics, the current is the exact Fourier transform of the memoryless Butler–Volmer law plus a linear capacitive term, and the series impedance acts harmonic by harmonic. No describing-function approximation and no time stepping.

Exact identity. For R_s = 0 the describing function is exactly Z₁(ω) = 1/(G_nl(A) + jωC_dl) — a Debye element — with G_nl(A) = (2i₀/b)·2I₁(A/b)/(A/b). A Debye satisfies Kramers–Kronig identically. The finite-amplitude spectrum is therefore KK-consistent by construction. Harmonic balance reproduces the Bessel identity to 10⁻¹⁷.

The falsifiable part. The numeric experiment shows the measured spectrum at 100 mV deviates from a perfect Debye by 9.6×10⁻⁸ relative — i.e. it is KK-consistent to eight digits — while the fitted charge-transfer resistance has fallen to 0.644 of its low-amplitude value. The classical Lin–KK residual does not track the bias at all (0.170 at 2 mV, 0.048 at 100 mV): it moves the wrong way.

Quantitative. R_ct/R_ct,true = 1.000 (2 mV), 0.996 (10 mV), 0.891 (50 mV), 0.644 (100 mV) for b = 51.4 mV. The third-harmonic ratio I₃/I₁ measures x = A/b to 0.2% at low frequency and converts directly into the correction. An amplitude-extrapolation protocol (four amplitudes, 0.5% noise) recovers the low-amplitude Re(Z₁) as 25 706 ± 79 against a true 25 701.

Refutation. R_ct amplitude-independent to 1% across 2–100 mV on a known Butler–Volmer system; or an I₃/I₁ that does not track the bias.

Limits. The mapping assumes a symmetric barrier and no mass transport. With α_a ≠ α_c a DC bias generates a second harmonic the symmetric model does not predict; with a Warburg element the harmonic current is loaded differently and the naive correction will over- or under-shoot. These are stated as open, not solved.

I3

Files. I3_kk_blindspot.py, data/i3_summary.json, figs/i3_kk.png.


Reproducing all three

cd blindspot-2026-11-01
export MPLCONFIGDIR=$PWD/../.mplconfig
../.venv-research/bin/python investigations/I1_offset_window_bias.py
../.venv-research/bin/python investigations/I2_boundary_bias.py
../.venv-research/bin/python investigations/I3_kk_blindspot.py
../.venv-research/bin/python investigations/R1_refinement_numbers.py

Dependencies: Python 3.14, numpy, scipy, matplotlib. No network access is required. The Monte Carlo seeds are fixed in the scripts (20261101, 7, 11), so the quoted means and standard deviations reproduce exactly.

Part II — Thirty refined hypotheses

Thirty hypotheses selected from the 300 for detailed development. Each entry states what is an identity (true by construction), what is a model artefact (a property of the analysis, not the world), and what is a genuine, falsifiable prediction. Quantitative values are computed by the scripts in investigations/; none is an experimental observation.


R01 — Finite-window decay exponents are set by the window, and the offset is recoverable from curvature

Refines X01. Sources: investigation I1; baseline-subtraction practice.

Claim. For a decay y(t) = At^(−α) + c with an unsubtracted offset c, the local log–log slope is exactly s(x) = −α/(1 + Be^{αx}) with B = c/A and x = ln t. A straight-line fit over a window therefore returns α_fit = α·⟨logistic⟩, where the average is taken with the least-squares weight.

What is an identity. The logistic form of s(x) is an identity — it follows from differentiating ln y. So is the result that a window centred on the crossover t_c = (A/c)^{1/α} returns exactly α_fit = α/2. This is not a discovery about nature; it is a property of the estimator, and it should be quoted as such.

What is a genuine prediction. Three things are not identities. (i) The bias is bounded: for a window entirely below the crossover the bias is <1% even at R = 1 decade, so the artefact cannot explain a literature-wide discrepancy unless the crossover lies inside the fitted range. (ii) The offset is identifiable from curvature: a three-parameter fit recovers α with zero bias (Monte-Carlo mean α_fit/α = 1.000 ± 0.011 at R = 3 decades, 2% noise) even when the two-parameter fit is 50% low. (iii) The Cramér–Rao bound diverges when the window sits below the crossover, so there is a hard limit on what any offset-blind analysis can claim.

Discriminating observation. Re-fitting a published decay with a free offset should shift the exponent, and the shift should be predicted by the fitted crossover. The diagnostic needs only the published data points.

Refutation. The hypothesis is refuted if published exponents are unchanged when a free offset is allowed and the log–log curvature is consistent with zero at the stated noise. If exponents move but the movement is not predicted by t_c, the mechanism is wrong even though the bias is real.

Limits. The analysis assumes additive, constant-variance noise in y. With multiplicative noise the bias changes sign structure; that case is not covered. A drifting (rather than constant) offset produces a time-dependent bias that the three-parameter fit cannot absorb — a genuine degeneracy, not an artefact of the fit.

Practical use. A two-line check on any reported power law: fit with and without a free offset, and report both. If they differ by more than the stated uncertainty, the exponent is a property of the window.


R02 — Kramers–Kronig consistency is not a linearity test

Refines C01. Sources: investigation I3; describing-function theory; arXiv:2605.08251 for the extrapolation analogue.

Claim. A Butler–Volmer interface shunted by a linear double-layer capacitance has a small-signal describing function that is exactly a Debye element with an amplitude-dependent conductance. It therefore satisfies Kramers–Kronig identically at every amplitude, while the charge-transfer resistance it returns is biased low by x/(2I₁(x)) with x = A/b.

What is an identity. With no series resistance, Z₁(ω) = 1/(G_nl(A) + jωC_dl) exactly, and the Bessel result G_app/G_true = 2I₁(x)/x is exact. Harmonic balance reproduces both to 1e-17 (validation in I3_kk_blindspot.py). None of this is new physics; it is the standard describing function of a symmetric exponential nonlinearity.

What is a genuine prediction. The combination — that the standard validity test cannot detect the bias — is falsifiable and non-obvious. Numerically, the finite-amplitude spectrum stays a Debye to 1e-7 relative even at 100 mV, while R_ct falls to 0.644 of its low-amplitude value (x = 1.95). A Lin–KK residual does not track the bias (0.170 at 2 mV, 0.048 at 100 mV): the test moves the wrong way.

Quantitative. R_ct/R_ct,true = 1.000 at 2 mV, 0.996 at 10 mV, 0.891 at 50 mV, 0.644 at 100 mV for b = 51.4 mV. The third-harmonic ratio I₃/I₁ measures x to 0.2% and converts directly into the correction.

Discriminating observation. On a reversible outer-sphere couple, R_ct should fall quadratically with amplitude with the predicted coefficient, while I₃/I₁ rises as x²/48.

Refutation. If R_ct is amplitude-independent to 1% across 2–100 mV on a system with a known Butler–Volmer response, the mechanism is absent. If R_ct varies with amplitude but I₃/I₁ does not track it, the mapping is wrong.

Limits. The mapping x → bias assumes a symmetric barrier and no mass transport. With asymmetric transfer coefficients a DC bias generates a second harmonic that the symmetric model does not predict; with a Warburg element in series the harmonic current is loaded differently and the naive correction will over- or under-shoot. Those cases are stated, not solved.

Practical use. Report R_ct at two amplitudes, or report I₃/I₁ alongside every impedance spectrum. Either costs one extra measurement and bounds a systematic that no KK test can see.


R03 — In-plane thermal conductivity from optical thermometry is a function of spot size, and in one limit it is not a material property at all

Refines M01. Sources: investigation I2; steady-state Raman thermometry modelling.

Claim. For a Gaussian source on a sheet with substrate conductance G, ΔT = (P/4πκd)·e^λE₁(λ) with λ = Gs²/(2κd). The standard fit returns κ_app = κ/[e^λE₁(λ)], which crosses unity at λ = 1 and asymptotes to κ_app ≈ Gs²/(2d).

What is an identity. The closed form is exact for the stated model — verified against direct Hankel quadrature to 2e-13. The asymptotic κ_app → Gs²/(2d) is a limit, not a new law.

What is a genuine prediction. The crossover λ = 1 corresponds to a spot radius s* = √(2κd/G): 0.58 µm for κ = 50 W/mK, d = 100 nm, G = 3×10⁷ W/m²K. That is squarely inside the operating range of Raman thermometers, so the bias changes sign across a typical experimental campaign. The prediction is a collapse: reported κ for one material should scale onto one curve when plotted against λ computed from each study’s spot radius, and should scale as s² for large spots.

Quantitative. For plausible (s, G) ranges the model produces a 136-fold spread in reported κ for a single true value. At λ = 1 the bias is +68%.

Discriminating observation. Reanalysis of a published κ compilation with spot radius and G metadata. The falsifiable signature is a slope of 2 on a log κ_app vs log s plot at large s.

Refutation. κ_app uncorrelated with spot radius across a compilation spanning 0.2–3 µm refutes the mechanism. So does a κ_app that is independent of the substrate.

Limits. The model is isotropic, steady-state, optically thin, and treats the substrate as a single conductance. Anisotropy, finite substrate thickness, and the transducer’s own boundary all add terms that are not modelled here; the 136-fold figure is an upper bound for the stated parameter range, not a prediction for any named material.

Practical use. Report the spot radius and the substrate conductance with every 2D κ measurement; fit λ rather than κ. Two spot sizes break the κ–G degeneracy — more laser powers do not (Cramér–Rao 0.037 at a 1:3 spot ratio vs rank-deficient at one spot).


R04 — Negative result: stray light does not explain OD600 compression in the exponential phase

Refines B01. Source: R1_refinement_numbers.py, section A.

Original claim. Plate-reader optical density compresses above ~0.3–0.6 because of detector saturation, suppressing fitted growth rates.

What the calculation shows. Modelling the reader as an additive stray-light fraction S, the fitted growth rate is suppressed by 0.1% for S = 10⁻³ over the window OD 0.2–1.0, and by 1.1% for S = 10⁻². The effect only becomes large where assays rarely operate: −8% for S = 10⁻³ and −23% for S = 10⁻² over OD 2.0–3.0.

Conclusion. The stray-light mechanism is real but confined to OD > 1.5. It cannot explain any compression at OD 0.3–0.6. The widely repeated warning about the linear range is, for this mechanism, misdirected.

What survives. Two things. First, the high-OD regime matters for anyone fitting late exponential phase or using long path lengths, and the correction is computable from the reader’s stray-light specification. Second, the absence of a stray-light explanation means any observed sub-exponential growth below OD 1 must come from a different mechanism — detector nonlinearity, meniscus and pipetting, evaporation, or a genuine physiological shift — and those are separable by the tests below.

Tests that would settle the residual. Fill-volume series (path length), gain series (detector), and sealed vs open plates (evaporation). If the apparent μ depends on fill volume at fixed gain, the mechanism is optical; if on gain only, electronic; if on sealing, evaporative.

Why this is kept. A hypothesis that fails a quantitative check is more useful than one that is merely plausible. The refinement narrowed a broad claim to a specific, quantified, high-OD regime and removed a mechanism from the list of suspects for the low-OD regime.


R05 — Four-bar conductivity measurements have an unbounded systematic from finite pad conductivity

Refines P09. Source: arXiv:2602.02418.

Claim. In a four-bar geometry the voltage-sensing pads are assumed to draw no current. When the pads have finite conductivity and the film is thin, current spreads into them, and the resulting error is not a contact resistance: it grows without bound as the film and pad conductivities approach each other.

Status of the result. The unboundedness is demonstrated in the cited work; my contribution here is the classification and the test design, not the derivation.

Why it is not a contact resistance. A contact resistance adds a series term that can be measured by varying the pad–film interface. Pad spreading adds a parallel path whose effect grows with the pad’s conductivity relative to the film’s; the two have different scaling with pad area and with film thickness, so a series-resistance calibration cannot remove it.

Discriminating observation. Extracted film conductivity should depend on pad metal at fixed film, with the discrepancy scaling as the conductivity ratio. It should also depend on pad width at fixed metal.

Refutation. Extracted conductivity invariant to pad material across a 100× conductivity range refutes the mechanism. So does invariance to pad width at fixed metal.

Limits. The effect is largest for highly conductive films on highly conductive pads — precisely the regime of transparent conductors and of metal films measured with lithographic leads. For semiconducting films with low-mobility pads the error may be negligible, which is why the practice survived.

Practical use. Report the pad/film conductivity ratio with every four-bar measurement, and use the van der Pauw geometry where the ratio is unfavourable.


R06 — Cryo-EM particle picking is confirmation-biased, and the bias scales with prior strength

Refines B05. Source: arXiv:2507.03951.

Claim. Template or network picking preferentially accepts images that already resemble the template. The selected subset is enriched in template-like views, which sharpens features present in the template and suppresses features absent from it.

Mechanism. Picking is a detection problem with a prior; the posterior over particle locations is conditioned on the template. The reconstruction then inherits a selection function whose shape is the template’s.

Genuine prediction. The bias is a function of prior strength, so a stronger prior (lower threshold, more distinctive template) should produce a larger discrepancy between the picked subset’s density and an independently determined one. Crucially, the effect is invisible in resolution metrics: a self-fulfilling map can be sharp.

Discriminating observation. Template-swap: reconstruct from subsets picked with two templates that differ in a specified region. The density in that region should differ, and the difference should scale with the templates’ difference. A second test: pick on a dataset before and after 3D classification and compare the maps’ densities for features absent from the initial template.

Refutation. Template-swapped reconstructions identical at the reported resolution refute the mechanism. So does a density that is invariant to picking threshold.

Limits. The cited work quantifies the bias; the magnitude for any given dataset depends on the template’s mismatch to the true particle, which is unknown a priori. The prediction is directional and scaling, not a universal number.

Practical use. Report the picking threshold and template; run a template-swap control on at least one region of interest.


R07 — Division by a noisy denominator manufactures a negative correlation that is routinely read as a trade-off

Refines X47. Source: R1_refinement_numbers.py, section C.

Claim. For a ratio X/Y with X and Y independent, corr(X/Y, Y) = −CV_Y/√(CV_X² + CV_Y² + CV_X²CV_Y²). The correlation is a property of the coefficient of variation, not of the biology or physics.

What is an identity. The formula is an identity for independent log-normal X and Y. It should be presented as a warning, not a discovery.

What is a genuine prediction. The magnitude is large in realistic regimes: −0.71 at CV = 0.1/0.1, −0.94 at 0.1/0.3, −0.32 at 0.3/0.1. The prediction is that measured “trade-offs” between a per-unit quantity and its denominator should weaken when the denominator’s precision improves, in a way fixed by the CV ratio.

Discriminating observation. Improve denominator precision by a known factor and re-measure the correlation. If the correlation is spurious, it should move along the predicted curve; if real, it should be unchanged.

Refutation. A correlation that is invariant to a tenfold improvement in denominator precision refutes the artefact explanation.

Limits. Log-normal marginals are assumed. With heavy-tailed denominators the exact form changes but the sign and order of magnitude do not. The artefact and a real trade-off can coexist; the test is designed to separate them, not to declare all such correlations spurious.

Practical use. Report CVs alongside any ratio–denominator correlation, and prefer log-ratio models.


R08 — Inverting a mean response through a curved calibration biases the mean input

Refines X45. Source: R1_refinement_numbers.py, section B.

Claim. For a calibration y = ax + bx², the mean response corresponds to an input above the mean input by ≈ (b/a)·σ_x². The error is second order in variability and first order in curvature.

What is an identity. This is Jensen’s inequality applied to the inverse calibration; the leading term is a Taylor expansion. It is not new mathematics.

What is a genuine prediction. The bias is large enough to matter in routine work: for b/a = 0.5 and CV = 0.6 the mean input is biased by 9%; for b/a = 0.2 and CV = 0.3 by 1.3%. The prediction is that two records with the same true mean but different variability will report different means, with a difference fixed by the curvature.

Discriminating observation. Compare high- and low-variability records at matched true mean; the inferred means should differ by the predicted amount. Alternatively, invert each sample before averaging and compare.

Refutation. Inferred means that are variability-independent for a calibration with measurable curvature refute the mechanism.

Limits. The expansion is first order in curvature; for strongly curved calibrations the full inverse must be integrated. The direction of the bias depends on the sign of b, so the test must use a calibration whose curvature sign is known.

Practical use. Average the input, not the response, whenever the calibration is curved — which is almost always.


R09 — Fitting in log space with additive noise biases the faint end upward and flattens slopes

Refines X15. Source: standard error-propagation result.

Claim. With additive Gaussian noise of variance σ², ln y is biased by −σ²/(2y²) — the bias is largest where y is smallest. A log-space fit therefore bends the faint end upward and reduces the fitted slope.

Status. This is a second-order delta-method identity. Its importance is practical: data spanning decades are almost always fitted in log space.

Genuine prediction. The slope bias is predictable from the relative noise at the faint end: a fit spanning a factor of 100 in y with 10% relative noise at the faint end should have its slope reduced by an amount computable from the noise profile. The prediction is quantitative and checkable on any published dataset that reports per-point uncertainties.

Discriminating observation. Refit the same data with a likelihood that matches the noise model (additive Gaussian in linear space) and compare slopes. The difference should match the delta-method prediction.

Refutation. Slopes that agree between log-space and correct-likelihood fits, for data with substantial relative noise at the faint end, refute the mechanism.

Limits. If the noise is genuinely multiplicative, log-space fitting is correct and the hypothesis does not apply. The test therefore requires knowing the noise model, which is often the unexamined assumption.

Practical use. State the noise model; fit in the space where the noise is homoscedastic.


R10 — Normalising to a reference imports that reference’s error into every sample

Refines X09. Source: compositional and reference-normalisation practice.

Claim. When measurements are expressed relative to a reference, the reference’s error is common to all normalised values and does not average out. It appears as a correlation between nominally independent samples.

Mechanism. Normalisation is a division by a random variable; the shared denominator induces a common factor whose variance is the reference’s relative variance.

Genuine prediction. The induced correlation is not removed by increasing the number of samples — only by increasing the reference’s precision or by using a reference-free model. The prediction is that inter-sample correlations should be invariant to which sample is chosen as reference if they are real, and should change sign or vanish under reference permutation if they are artefacts.

Discriminating observation. Reference-permutation analysis: recompute the correlation matrix with each sample in turn as the reference. A real correlation is stable; an artefact moves.

Refutation. Correlations invariant to reference permutation, in a dataset where the reference’s own CV is large, refute the mechanism.

Limits. If the reference is measured much more precisely than the samples (a certified standard), the imported error is negligible and the hypothesis does not apply.

Practical use. Permute the reference before reporting any correlation from normalised data.


R11 — Two interface conductances in a TDTR stack are never separable at one modulation frequency

Refines M03. Source: R1_refinement_numbers.py, section I (thermal quadrupole).

Claim. In a transducer/film/substrate stack with two interface conductances, a single-frequency measurement determines only a weighted combination. The weighting is set by the resistances’ share of the total thermal impedance, and it changes with modulation frequency only because the film’s heat capacity introduces a frequency-dependent element.

Computation. A 1D thermal-quadrupole model (Al transducer 80 nm, film 100 nm, G₁ = 10⁸, G₂ = 5×10⁷ W/m²K) gives S_G2/S_G1 = 2.02 at 100 kHz falling to 0.55 at 30 MHz. The ratio changes by a factor of 3.7 across the band, which is what makes a multi-frequency fit possible at all.

What is an identity. That two series resistances are inseparable at a single frequency is elementary. The quantitative ratio and its frequency dependence are model results.

Genuine prediction. The fitted G should drift with modulation frequency in the direction and by the amount predicted by the sensitivity ratio, and should stabilise only when the fit includes enough of the band to constrain both terms. A corollary prediction: reported G values for the same interface measured at different frequencies should differ systematically, and the difference should be larger for thinner films (where the heat capacity term is weaker).

Discriminating observation. Frequency-series TDTR on a sample with independently characterised transducer adhesion.

Refutation. A fitted G that is frequency-independent across 100 kHz–30 MHz, for a film thin enough that both boundaries contribute, refutes the mechanism.

Limits. The model is 1D and isotropic; radial heat flow and anisotropic films add terms. The specific ratios depend on the assumed conductivities and are illustrative, not universal.

Practical use. Fit the full frequency series with both conductances free; report the sensitivity ratio so readers can see which boundary dominates.


R12 — Metal–dielectric thermal boundary conductance measured on thin films includes the electron–phonon resistance

Refines M38. Source: two-temperature model practice.

Claim. Heat must equilibrate between electrons and phonons in the metal over a finite length. For metal films thinner than that length, the measured interface conductance includes the electron–phonon resistance in series, and the reported G depends on metal thickness.

Mechanism. Two resistances in series: the interface and the electron–phonon channel. The second scales with thickness, so a thickness series separates them without any additional measurement.

Genuine prediction. G_app should increase with metal thickness and saturate at the electron–phonon length, which is tens of nanometres for typical metals. The saturation length is a material property and should be the same for different substrates at fixed metal.

Discriminating observation. Metal-thickness series at fixed substrate and fixed interface preparation.

Refutation. G independent of metal thickness below 20 nm refutes the mechanism for that system.

Limits. The electron–phonon length depends on temperature and on the electron mean free path, so the test must be at fixed temperature. For thick films the effect vanishes, which is why it survived: most TDTR work uses 60–100 nm transducers where the correction is small but not zero.

Practical use. Use two transducer thicknesses, or correct with the known electron–phonon coupling constant.


R13 — Amorphous films thinner than the dominant phonon mean free path have suppressed thermal conductivity

Refines M45. Source: thermal-conductivity suppression literature.

Claim. Surface scattering removes the low-frequency modes that carry most of the heat in amorphous films. For thicknesses below the dominant mean free path the conductivity is suppressed, and the suppression follows a thickness-dependent function.

Genuine prediction. κ should decrease below a threshold thickness and should be lower for rougher surfaces at the same thickness. The threshold is material-specific and is not a universal constant.

Discriminating observation. Thickness series with independently measured surface roughness.

Refutation. κ independent of thickness above 5 nm for a material whose dominant mean free path is known to be 50 nm refutes the mechanism.

Limits. In amorphous materials the mean free path is ill-defined and is itself a fitted quantity, so the prediction is a functional form rather than a number. Interface layers and oxidation can mimic the effect.


R14 — The constant-phase exponent of a porous electrode is a geometry parameter, not a roughness parameter

Refines C35. Source: porous-electrode transmission-line models.

Claim. In a porous electrode with a distributed RC transmission line, the impedance is a power law over the frequency range where the penetration depth lies inside the pore. That power law mimics a constant-phase element with exponent 0.5–0.9, and the exponent is set by pore geometry.

Genuine prediction. The CPE exponent should change with electrode thickness at fixed material, following the transmission-line prediction; a roughness-driven CPE would be thickness-independent.

Discriminating observation. Thickness series of the same electrode material, with the exponent fitted over a fixed frequency band.

Refutation. Exponent independent of thickness, in a material with measurable pore-length polydispersity, refutes the geometric explanation.

Limits. Both mechanisms can operate at once, and the transmission-line model requires an assumption about the pore-size distribution. The test separates the dominant term, not the two contributions exactly.


R15 — The low-frequency tail of an impedance spectrum is drift, not diffusion

Refines C18. Source: drift artefacts in low-frequency EIS.

Claim. Slow drift of the open-circuit potential over the minutes-to-hours of a low-frequency sweep produces a current ramp whose demodulated quadrature component is ∝ 1/ω — indistinguishable, in a single sweep, from a Warburg or CPE element.

Mechanism. The lock-in demodulation of a linear ramp over an integration time T produces a quadrature signal proportional to the ramp rate times T. Because T is itself proportional to 1/ω for a swept measurement, the artefact is ∝ 1/ω.

Genuine prediction. Reversing the sweep direction should change the sign of the low-frequency tail while leaving the mid-frequency arc intact. A true diffusion element is direction-independent.

Discriminating observation. Forward and reverse sweeps at fixed DC bias, with the DC drift monitored independently.

Refutation. Identical forward and reverse low-frequency tails refute the drift explanation.

Limits. A genuine Warburg and drift can coexist; the direction test separates them only if the drift is monotonic over the sweep time. Galvanostatic operation changes the artefact’s form.

Refined hypotheses R16–R30

Continuation of R01–R15.md. Same conventions: identities and model artefacts are labelled, quantitative values come from investigations/, and no experiment has been performed.


R16 — Open-circuit voltage cannot give state of charge until the diffusion relaxation is complete

Refines E28. Source: OCV–SOC hysteresis literature.

Claim. OCV is read after a fixed rest and mapped to SOC. Diffusion relaxation in thick electrodes takes hours; a one-hour rest leaves a voltage offset whose sign depends on the preceding current direction.

Mechanism. The electrode’s solid-phase concentration profile relaxes with a spectrum of time constants set by particle radius and diffusivity. The terminal voltage is a functional of the surface concentration, which is not the mean concentration until relaxation completes.

Genuine prediction. The OCV–SOC curve measured after charge lies systematically above the curve measured after discharge, and the gap closes with rest time in a way that scales as the particle diffusion time. The prediction is quantitative for a given particle size: the gap should shrink by a factor of e when rest time increases by the diffusion time.

Discriminating observation. Rest-duration series after charge and after discharge on the same cell, at several SOCs.

Refutation. OCV independent of prior current direction after a one-hour rest refutes the mechanism for that electrode.

Limits. For thin electrodes or high-diffusivity materials the relaxation is fast and the artefact is negligible. The mapping from rest time to relaxation is model-dependent.

Practical use. Report rest time and prior direction with every OCV–SOC point; use a relaxation model rather than a lookup table.


R17 — Surface-plasmon resonance affinities are limited by mass transport, and the limitation survives a good global fit

Refines B16. Source: mass-transport limitation in SPR.

Claim. Mass-transport limitation produces a response that is well fitted by a 1:1 model with a reduced k_on, because both effects saturate. The fit residual is small while k_on is underestimated, by up to an order of magnitude.

Mechanism. The analyte flux to the surface is bounded by diffusion through the depletion layer. When the reaction is faster than transport, the observed rate is the transport rate, and the 1:1 model absorbs it.

Genuine prediction. k_on should increase with flow rate and saturate, and should approach the true value when ligand density is reduced. The dependence on ligand density is the discriminating one: transport limitation scales with the Damköhler number, which is proportional to ligand density.

Discriminating observation. Flow-rate and ligand-density series on the same interaction.

Refutation. k_on invariant to flow rate and ligand density refutes the mechanism.

Limits. At very low ligand density the signal-to-noise falls, so the test has a practical floor. The Damköhler number must be estimated from the measured k_on, which is circular unless an independent estimate of the transport coefficient is available.

Practical use. Report ligand density and flow rate; run one injection at a different flow rate as a control.


R18 — Bolometer time constants measured in situ are biased by the optical load they are meant to characterise

Refines P22. Source: electrothermal TES modelling.

Claim. Transition-edge sensor response is electrothermal; the effective time constant depends on bias power and hence on optical load. A constant measured at high calibration load is shorter than the sky-load value, biasing beam-map deconvolution for fast scans.

Genuine prediction. Time constants should vary with controlled load (aperture cover) with a slope predictable from the electrothermal model, and map transfer functions should depend on scan speed accordingly.

Discriminating observation. Load-variation campaign, with the same detector measured under several aperture states and at several scan speeds.

Refutation. Time constant invariant to load within 1% refutes the mechanism for that detector.

Limits. The electrothermal model requires the detector’s bias circuit parameters, which are not always reported. The prediction is directional and scaling, not a universal constant.


R19 — NV thermometry has a strain–temperature degeneracy whose size depends on the crystal cut

Refines P08. Source: Zenodo 21299294 (pre-registered NV thermometry comparison).

Claim. Axial strain and temperature both shift the zero-field splitting D. The two contributions are collinear for a [100]-cut ensemble but not for [111], so a single-axis measurement reports a temperature error proportional to the local strain.

Mechanism. The spin-strain tensor’s axial component adds to D; the temperature coefficient is also a shift in D. For one orientation the two enter with the same sign and cannot be separated; for another they differ in sign or magnitude.

Genuine prediction. Temperature readings from [100] and [111] ensembles on the same sample should disagree under applied stress and agree stress-free. The disagreement should be linear in the applied strain with a coefficient set by the spin-strain coupling.

Discriminating observation. Dual-orientation diamond with a piezoelectric strain stage.

Refutation. Both cuts tracking the same temperature within 0.1 K under 10⁻⁴ strain refutes the mechanism.

Limits. The comparison requires two ensembles in the same local strain field, which is itself difficult. The published comparison of 23 methods reports geometric blind spots that are consistent with this mechanism but do not isolate it.


R20 — A forgotten trend deflates error bars, but only modestly

Refines X13. Source: R1_refinement_numbers.py, section G.

Claim. Error bars on a time average use an autocorrelation time estimated from the same record. Detrending removes the variance that dominates the uncertainty.

Calculation. For a record with a linear ramp of amplitude a and noise σ, the true standard error of the mean is √(a²/12 + σ²), while the naive estimate from residuals is σ. The underestimate factor is 1.01 for a/σ = 0.5, 1.15 for a/σ = 2, and 1.53 for a/σ = 4.

Correction to the original claim. The effect is smaller than the original entry implied. It matters only when the trend dominates the noise (a/σ ≳ 2) and even then deflates the error bar by less than a factor of two. The original entry overstated the generality.

What survives. For records where the trend is several times the noise — which is exactly the case in long environmental and astrophysical series — a 50% underestimate is worth correcting, and the correction is analytically available.

Discriminating observation. Compare single-record error estimates against ensemble estimates from replicate records; the ratio should follow the predicted curve in a/σ.

Refutation. Ratio equal to one for a/σ = 4 refutes the mechanism.

Limits. The calculation assumes a linear trend and white noise. Red noise changes the arithmetic but not the direction.


R21 — Inverse-variance weighting with estimated variances does not bias the mean, but understates its uncertainty

Refines X33. Source: R1_refinement_numbers.py, section H (Monte Carlo, 40 000 trials).

Original claim. Weighting by inverse estimated variance biases the weighted mean toward points whose noise fluctuated low.

What the simulation shows. The mean is unbiased (mean −0.000 to 0.005 across 2–30 degrees of freedom). What changes is the spread: the estimator’s standard deviation is 0.686 at 2 dof, 0.582 at 5, 0.539 at 10, 0.511 at 30, against a nominal 0.5. The quoted uncertainty is therefore 73%, 86%, 93%, 98% of the true spread.

Correction. The hypothesis as stated is wrong about the mean and right about the uncertainty, with a magnitude that depends on the degrees of freedom used to estimate each variance.

Genuine prediction. Reported weighted means with per-point variances estimated from few replicates should show excess scatter across repeated experiments, by the predicted factor, while their central values remain unbiased. The prediction is testable on any replicated meta-analysis.

Discriminating observation. Replication scatter versus quoted uncertainty, stratified by the dof used per point.

Refutation. Scatter matching the quoted uncertainty for dof = 2 refutes the mechanism.

Limits. The simulation uses Gaussian data and four measurements per dataset; other configurations shift the numbers but not the structure.


Refines B39 / X11. Source: censored-data methods.

Claim. Substituting a constant for values below the limit compresses the low end. If the quantity is increasing over time, the censored fraction falls, so the substituted values occupy less of the record and the trend is biased by an amount that depends on the censoring fraction’s trend.

Mechanism. Substitution is a biased estimator of the conditional mean below the limit; the bias enters the trend through the changing mixture weight.

Genuine prediction. The trend estimated with a censored-data likelihood should differ from the substitution estimate by an amount that scales with the change in censoring fraction across the record, not with its average. A record with constant censoring shows no bias even if heavily censored.

Discriminating observation. Reanalysis of time series with reported detection limits and censoring fractions.

Refutation. Trends unchanged under a censored likelihood, in a record whose censoring fraction changes by a factor of two, refutes the mechanism.

Limits. The bias direction depends on the substitution rule (LOD/2, LOD/√2, deletion); the prediction should be made for the rule actually used, which is often not stated.


R23 — Low-cost particle sensors report a humidity-driven mass that mimics winter pollution

Refines E01. Source: low-cost sensor correction literature.

Claim. Hygroscopic growth increases the optical diameter at high relative humidity. The reported PM₂.₅ rises with RH at constant mass, and a co-location calibration over a narrow humidity range cannot identify the coefficient.

Mechanism. Optical scattering scales steeply with diameter; deliquesced aerosol scatters more per unit dry mass. The growth factor is a known function of RH (κ-Köhler), so the artefact is predictable from the aerosol’s hygroscopicity.

Genuine prediction. The sensor/reference ratio at fixed reference PM should correlate with RH with a slope independent of site, and the slope should scale with the aerosol’s κ. The prediction is that a network’s seasonal cycle contains an RH-shaped component that is absent from the reference.

Discriminating observation. Co-location data spanning a full humidity range, ideally at two sites with different aerosol hygroscopicity.

Refutation. Ratio independent of RH across sites refutes the mechanism.

Limits. The growth factor depends on composition, which varies; a single correction will not be exact. The prediction is a systematic shape, not a point correction.


R24 — DSC onset temperatures shift with scan rate by an amount set by the pan–sample time constant

Refines C25. Source: R1_refinement_numbers.py, section F.

Claim. The measured onset is the true onset plus τβ, where τ is the effective pan–sample thermal time constant and β the scan rate. With τ = 5–20 s the shift is 0.4–6.7 K over 5–20 K/min.

Mechanism. The sample’s temperature lags the programmed temperature by τ; the onset criterion is applied to the programmed value.

Genuine prediction. The onset should be linear in scan rate with slope τ, and τ should scale with sample mass and with pan–sample contact. Zero-rate extrapolation recovers the true onset only if the relation is linear, which fails when the pan’s thermal resistance is comparable to the sample’s.

Discriminating observation. Scan-rate and mass series on the same material.

Refutation. Onset independent of scan rate for a sample with a measurable thermal lag refutes the mechanism.

Limits. The time constant is not directly measurable in a standard DSC; the test infers it from the slope, which is the quantity of interest.


R25 — Permeability assays measure the unstirred water layer as much as the monolayer

Refines B42. Source: R1_refinement_numbers.py, section E.

Claim. P_app⁻¹ = P_true⁻¹ + P_UWL⁻¹ with P_UWL = D/h. For a 1000 µm unstirred layer and D = 5×10⁻⁶ cm²/s, P_UWL ≈ 5×10⁻⁵ cm/s; a compound with P_true = 5×10⁻⁴ cm/s is reported at 9% of its true value.

What is an identity. The series-resistance formula is elementary.

What is a genuine prediction. The distortion is compound-dependent and predictable: the ratio P_app/P_true falls from 0.91 for P_true = 5×10⁻⁶ cm/s to 0.09 for 5×10⁻⁴ cm/s at h = 1000 µm. Shaking reduces h and therefore moves the ratio toward 1 for permeable compounds only. The prediction is that in-vitro/in-vivo correlations improve when P_app is corrected for the measured h, and that the correction matters only above a threshold permeability.

Discriminating observation. Shaking-rate series across a compound panel of graded permeability.

Refutation. P_app independent of shaking rate for permeable compounds refutes the mechanism.

Limits. D must be known or estimated; h is not directly measured in most assays. The series model assumes a uniform layer.

Practical use. Report shaking rate; include at least one high-permeability reference compound to expose the layer.


R26 — Dielectric breakdown strength scales with electrode area, so reported strengths are not material properties

Refines M33. Source: R1_refinement_numbers.py, section D.

Claim. Breakdown is defect-initiated, so the Weibull scale parameter scales as (A/A₀)^(−1/m). For m = 10, a 100× area increase reduces the reported strength to 63% of the small-area value; for m = 5, to 40%.

What is an identity. The area scaling is a standard result of weakest-link statistics.

What is a genuine prediction. The slope 1/m is measurable from an area series and is a property of the defect population, not of the material’s intrinsic strength. The prediction is that interlaboratory scatter in reported breakdown strength should collapse when normalised to a common area, and that the collapse should be exact only when the defect populations are similar.

Discriminating observation. Area series in one laboratory, then comparison of normalised values across laboratories.

Refutation. Scale parameter independent of area, for a material with a measurable defect density, refutes the mechanism.

Limits. The Weibull model assumes a single defect population; multimodal defect distributions produce curvature in the area plot that the single-m gives incorrectly.

Practical use. Report electrode area and the fitted Weibull modulus with every breakdown strength.


R27 — Interferometric total flux is set by the shortest baselines, so flux errors are not constrained by closure quantities

Refines P42. Source: wide-field interferometric calibration.

Claim. Total flux is carried by the shortest baselines, where the primary beam and the wide-field term are largest. A fractional error in the shortest-baseline gain moves total flux without changing image shape, and closure quantities do not constrain it.

Mechanism. Closure phase and closure amplitude are invariant to station-based gains. A common gain error across all short baselines is therefore invisible to closure but changes the total flux.

Genuine prediction. Total flux should correlate with the shortest-baseline gain solution, and should differ between imaging with and without short baselines (tapering). The prediction is that the flux scale error is a function of the array’s minimum baseline, not of its maximum.

Discriminating observation. Re-image the same dataset with and without tapering, and compare total flux against an independent (single-dish) measurement.

Refutation. Total flux invariant to tapering and to shortest-baseline gain refutes the mechanism.

Limits. For resolved sources, tapering also changes the recovered flux through missing extended structure, so the two effects must be separated with a source model.


R28 — Cycloheximide chase half-lives are shorter than degron-based half-lives for the same protein

Refines B13. Source: comparison of translation-inhibition methods.

Claim. Cycloheximide perturbs the cell within minutes; the chase’s t = 0 is defined after the perturbation, so the fitted decay includes a fast stress component.

Genuine prediction. Half-lives from cycloheximide should be systematically shorter than from an auxin-inducible degron for the same protein, and the difference should scale with the induction of a stress marker. The prediction is comparative: the two methods should converge for proteins whose degradation is stress-insensitive.

Discriminating observation. Side-by-side chase with both methods on a panel of proteins of known stability, with a stress-marker readout.

Refutation. Half-lives agreeing across methods for stress-sensitive proteins refutes the mechanism.

Limits. Degron systems have their own artefacts (auxin effects, tag effects on stability). The test is a triangulation, not a gold standard.


R29 — Ozonesonde records contain an instrument-generation trend from pump efficiency

Refines E15. Source: ozonesonde homogenisation literature.

Claim. Pump efficiency falls with reduced pressure and with contamination. The correction depends on sonde age and on the launch profile, so a fleet that changes generation acquires a trend confounded with the atmospheric one.

Genuine prediction. The sonde-to-satellite or sonde-to-lidar ratio should differ between generations after the standard correction, and the difference should be largest in the upper troposphere–lower stratosphere where the pump works hardest.

Discriminating observation. Intercomparison campaigns with sondes from two generations launched together.

Refutation. Ratios independent of generation after standard correction refute the mechanism.

Limits. Generation changes usually coincide with other changes (sensor chemistry, launch practice), so isolation requires a deliberate side-by-side campaign.


R30 — A global fit absorbs unmodelled physics into whichever parameter is most flexible

Refines X30. Source: model-dependence of fitted constants.

Claim. The covariance matrix reflects only the parameters in the model. Unmodelled physics is absorbed by the most flexible parameter, which then appears both precise and shifted. Its precision is a statement about the model’s rigidity, not about the measurement.

Mechanism. The fit projects the model discrepancy onto the parameter space along the direction of least resistance. That direction is set by the model’s structure, not by the data.

Genuine prediction. The parameter should shift by more than its quoted uncertainty when the model is extended with physically motivated terms, and the shift should be largest for the parameter with the largest flexibility (as measured by the width of its posterior under the original model). A corollary: parameters with narrow posteriors are the most likely to be absorbing discrepancy, not the best measured.

Discriminating observation. Model-extension sensitivity on a published fit: add one physically motivated term and record which parameter moves.

Refutation. Parameters stable under physically motivated extensions refute the mechanism.

Limits. The test requires a physically motivated extension, which is exactly what may be missing. A parameter that is stable under every extension the community has tried is evidence for robustness, not proof of it.

Part III — Three hundred hypotheses

Every entry below is a proposition, not a report of a measurement. No experiment described here has been performed.

P01 — The quadratic-Zeeman correction does not extrapolate because it is an average, not a point value

physics.atom-ph · hidden-parameter · readiness 3 · novelty 3

P02 — Detector calibration measured at high actuation amplitude biases every loud event

physics.ins-det · nonlinearity · readiness 4 · novelty 3

P03 — Dispersion-measure variations absorb scattering and manufacture red noise

astro-ph.HE · model-disagreement · readiness 4 · novelty 3

P04 — Planet-based beam calibration is biased by the finite planet disc in a frequency-dependent way

astro-ph.IM · boundary-condition · readiness 3 · novelty 2

P05 — Cepheid crowding corrections carry a distance-independent bias that mimics a Hubble-tension shift

astro-ph.CO · selection · readiness 3 · novelty 3

P06 — Zero-noise extrapolation fails when the noise is non-Markovian, and the failure is measurable

quant-ph · assumption · readiness 4 · novelty 3

P07 — Randomized benchmarking is blind to drift because it assumes gate-independent error

quant-ph · time-dependent · readiness 4 · novelty 3

P08 — NV thermometry has a strain–temperature degeneracy fixed by the crystal cut

cond-mat.mes-hall · degeneracy · readiness 4 · novelty 3

P09 — Four-bar conductivity measurements have an unbounded error from finite contact pads

cond-mat.mtrl-sci · boundary-condition · readiness 5 · novelty 2

P10 — Single-photon detector efficiency calibrations inherit a bias from afterpulsing that depends on count rate

physics.ins-det · nonlinearity · readiness 4 · novelty 3

P11 — Two accepted measurements of the neutron lifetime differ because one of them measures a surface, not a volume

nucl-ex · model-disagreement · readiness 3 · novelty 3

P12 — Exoplanet radius valley positions are biased by the limb-darkening law used in transit fits

astro-ph.EP · assumption · readiness 4 · novelty 3

P13 — Supernova standardisation coefficients are window-dependent because colour and stretch are not orthogonal in the observed frame

astro-ph.CO · hidden-parameter · readiness 3 · novelty 3

P14 — The X-ray mass proxy is biased by clumping in a way that is degenerate with feedback

astro-ph.CO · assumption · readiness 3 · novelty 3

P15 — Line-of-sight velocity dispersion estimates are biased by binary orbits in a way that depends on the observing window

astro-ph.GA · time-dependent · readiness 4 · novelty 3

P16 — Quantum-advantage demonstrations are compared against a classical baseline that is not optimised to the same error model

quant-ph · model-disagreement · readiness 4 · novelty 3

P17 — Maser clocks and optical clocks disagree through a temperature coefficient that is attributed to the wrong component

physics.atom-ph · hidden-parameter · readiness 3 · novelty 3

P18 — Interferometric null tests pass while the systematic is common-mode

physics.optics · blind-spot · readiness 4 · novelty 3

P19 — The cosmic-ray energy scale is set by a calorimeter that is not calorimetric at the highest energies

astro-ph.HE · assumption · readiness 3 · novelty 3

P20 — Optical-clock comparisons inherit an unmodelled self-gravity term that depends on the apparatus mass, not on the site

physics.atom-ph · hidden-parameter · readiness 3 · novelty 3

P21 — Matter-wave interferometry’s contrast loss is attributed to decoherence but is partly a classical alignment drift

physics.atom-ph · time-dependent · readiness 3 · novelty 3

P22 — Bolometer time constants measured in-situ are biased by the optical load they are meant to characterise

astro-ph.IM · nonlinearity · readiness 4 · novelty 3

P23 — Aperture-synthesis closure phases are immune to some systematics and therefore blind to them

astro-ph.IM · blind-spot · readiness 3 · novelty 3

P24 — The neutrino mass ordering significance depends on the reactor flux model used to normalise, not on the data

hep-ex · model-disagreement · readiness 3 · novelty 3

P25 — Black-hole ringdown overtones are contaminated by the merger’s nonlinear phase, and the contamination looks like a higher-overtone amplitude

gr-qc · assumption · readiness 3 · novelty 3

P26 — Quantum-noise squeezing levels are quoted at a photodiode that does not see the mode the interferometer uses

physics.optics · calibration-degeneracy · readiness 4 · novelty 3

P27 — The solar abundance scale is set by a 3D/non-LTE correction that is calibrated on one line, then applied to all

astro-ph.SR · model-disagreement · readiness 3 · novelty 3

P28 — Cosmic shear shear-calibration bias is a function of galaxy size, and size correlates with redshift

astro-ph.CO · boundary-condition · readiness 4 · novelty 3

P29 — Dark-siren cosmology is limited by the lensing-magnification prior, not by the catalogue size

gr-qc · hidden-parameter · readiness 3 · novelty 3

P30 — The Tully–Fisher zero point and the Cepheid zero point disagree because of a common saturation term

astro-ph.GA · model-disagreement · readiness 3 · novelty 3

P31 — Finite simulation box size biases the inferred dark-matter annihilation boost in a direction that depends on the observable

astro-ph.CO · boundary-condition · readiness 3 · novelty 3

P32 — Vacuum-systematic bounds in atom interferometry are limited by an unmeasured pressure gradient

physics.atom-ph · hidden-parameter · readiness 3 · novelty 3

P33 — Superconducting qubit coherence is limited by a thermal population that the thermometer cannot see below 50 mK

quant-ph · blind-spot · readiness 3 · novelty 3

P34 — The local Hubble flow is measured with a zero point that depends on the same peculiar-velocity model it is used to test

astro-ph.CO · circularity · readiness 3 · novelty 3

P35 — Radiometric calibration of a spectrometer’s slit function hides a wavelength-dependent bias in retrieved column densities

physics.optics · assumption · readiness 4 · novelty 2

P36 — The proton radius puzzle’s remaining discrepancy is a fit-range artifact in the extraction of the charge radius from form factors

nucl-ex · model-disagreement · readiness 3 · novelty 3

P37 — Scintillator quenching corrections are calibrated in a beam that does not reproduce the dE/dx spectrum of the application

physics.ins-det · extrapolation · readiness 3 · novelty 2

P38 — The neutron electric-dipole-moment systematic budget omits a motional-field term that scales with the dressing-field gradient

physics.atom-ph · hidden-parameter · readiness 3 · novelty 3

P39 — The extragalactic background light is bounded by a gamma-ray opacity that is degenerate with intergalactic magnetic-field heating

astro-ph.HE · degeneracy · readiness 3 · novelty 3

P40 — Stellar rotation periods from spot modulation alias to half the true period when the spot lifetime exceeds the observing baseline

astro-ph.SR · time-dependent · readiness 4 · novelty 2

P41 — Fast-radio-burst fluence distributions are truncated by the detection pipeline’s dedispersion incoherence

astro-ph.HE · selection · readiness 4 · novelty 3

P42 — Interferometric imaging’s flux-scale error is set by the shortest baseline, not by the longest

astro-ph.IM · boundary-condition · readiness 3 · novelty 3

P43 — Muon tomography’s density inversion is biased by the assumed rock composition, and the bias is degenerate with a void

physics.ins-det · degeneracy · readiness 3 · novelty 2

P44 — The quantum Cheshire Cat and similar weak-value experiments are null tests that cannot distinguish disturbance from signal

quant-ph · blind-spot · readiness 3 · novelty 3

P45 — Lunar laser ranging’s station bias is a function of the retroreflector array orientation, which is not modelled

gr-qc · boundary-condition · readiness 3 · novelty 3

P46 — Superconducting transition-temperature measurements inherit a strain state from the mounting that is never reported

cond-mat.supr-con · hidden-parameter · readiness 4 · novelty 3

P47 — The 21-cm global signal’s foreground removal leaves a bias set by the beam chromaticity, not by the foreground model

astro-ph.CO · model-disagreement · readiness 3 · novelty 3

P48 — The neutron-star radius inference from pulse-profile modelling is degenerate with the hotspot’s beaming function

astro-ph.HE · degeneracy · readiness 3 · novelty 3

P49 — Scanning-probe thermometry measures the tip–sample interface, not the sample

cond-mat.mes-hall · boundary-condition · readiness 3 · novelty 3

P50 — The cosmological constant from supernova residuals is degenerate with a calibration step that is fitted per-season

astro-ph.CO · hidden-parameter · readiness 3 · novelty 3

Chemistry and electrochemistry — 50 hypotheses

Every entry is a proposition. No experiment below has been performed.

C01 — Kramers–Kronig consistency is not a linearity test, so reported charge-transfer resistances are amplitude artefacts

electrochem · nonlinearity · readiness 5 · novelty 4

C02 — The double-layer capacitance extracted from impedance includes a faradaic contribution that scales with amplitude

electrochem · model-disagreement · readiness 4 · novelty 3

C03 — Tafel slopes are biased by uncompensated resistance in a way that mimics a change of mechanism

electrochem · hidden-parameter · readiness 5 · novelty 3

C04 — Reported turnover frequencies depend on the assumed electrochemically active surface area, which is itself measured by a process that changes the surface

electrochem · circularity · readiness 4 · novelty 3

C05 — Solvent isotope effects on rate constants are contaminated by a viscosity change that is not corrected

physical-chem · hidden-parameter · readiness 4 · novelty 3

C06 — Arrhenius activation energies from narrow temperature ranges are systematically inflated by a hidden curvature

physical-chem · assumption · readiness 5 · novelty 2

C07 — Catalytic selectivity reported at low conversion is not the selectivity of the catalyst

chem-eng · boundary-condition · readiness 4 · novelty 2

C08 — The pH measured in a buffered microdroplet is not the pH that governs the reaction

physical-chem · boundary-condition · readiness 4 · novelty 3

C09 — Standard reduction potentials from computational hydrogen electrode calculations hide a potential-dependent solvation that changes the mechanism assignment

computational-chem · model-artifact · readiness 4 · novelty 3

C10 — Reaction calorimetry’s baseline subtraction removes a heat of mixing that is not constant

analytical-chem · time-dependent · readiness 4 · novelty 2

C11 — Chromatographic retention indices drift because the dead-time marker is retained

analytical-chem · hidden-parameter · readiness 4 · novelty 2

C12 — Photocatalytic quantum yields above unity are artefacts of a light-absorption measurement made on a suspension

photochem · calibration · readiness 4 · novelty 3

C13 — Isotope-labelling product distributions are biased by scrambling in the inlet, not in the catalyst

catalysis · model-artifact · readiness 4 · novelty 3

C14 — The electrochemical CO₂ reduction faradaic efficiency is normalised to a charge that includes a parasitic corrosion current

electrochem · hidden-parameter · readiness 4 · novelty 3

C15 — Battery Coulombic efficiency measured by cycling includes a self-discharge term that scales with rest time

electrochem · time-dependent · readiness 4 · novelty 3

C16 — Spectroscopic binding constants from titration are biased by inner-filter effects that depend on the binding itself

analytical-chem · circularity · readiness 4 · novelty 3

C17 — The glass-transition temperature from DSC depends on the fictive temperature, which is set by the prior thermal history and rarely reported

materials-chem · hysteresis · readiness 5 · novelty 2

C18 — Electrochemical impedance’s low-frequency tail is drift, not diffusion

electrochem · time-dependent · readiness 5 · novelty 3

C19 — X-ray absorption edge positions shift with sample thickness through self-absorption, and the shift is read as an oxidation-state change

synchrotron · boundary-condition · readiness 4 · novelty 3

C20 — Raman-based temperature and strain measurements in operando cells are degenerate

spectroscopy · degeneracy · readiness 4 · novelty 3

C21 — The turnover number in photocatalysis is computed against a catalyst mass that changes during the reaction

photochem · hidden-parameter · readiness 4 · novelty 2

C22 — Electron-spin-resonance quantification of radicals ignores a temperature-dependent cavity filling factor

spectroscopy · calibration · readiness 4 · novelty 2

C23 — The rate of a bimolecular reaction in a nanoreactor is reported per volume but governed by an interfacial concentration

physical-chem · boundary-condition · readiness 4 · novelty 3

C24 — The oxygen evolution overpotential includes a bubble-coverage term that is a function of the electrode’s history

electrochem · time-dependent · readiness 4 · novelty 3

C25 — Differential scanning calorimetry’s melting point is biased by thermal lag that is proportional to the sample mass and to the scan rate

thermal-analysis · boundary-condition · readiness 5 · novelty 2

C26 — N₂ physisorption surface areas of microporous carbons depend on the adsorptive, and the BET model is applied outside its validity range

materials-chem · assumption · readiness 5 · novelty 2

C27 — The apparent activation energy of a supported catalyst changes with metal loading because the rate is diffusion-masked at high loading

catalysis · hidden-parameter · readiness 4 · novelty 3

C28 — The pKa of a surface site derived from titration depends on the ionic strength through a double-layer term that is not fitted

physical-chem · hidden-parameter · readiness 4 · novelty 3

C29 — Photoluminescence quantum yield measured in a film includes reabsorption, which depends on film thickness and on the overlap integral

photochem · boundary-condition · readiness 4 · novelty 3

C30 — The “intrinsic” conductivity of a doped polymer is dominated by intergrain barriers whose width is set by the dopant’s hygroscopicity

materials-chem · boundary-condition · readiness 3 · novelty 3

C31 — The fluorescence lifetime from TCSPC is biased by the instrument response’s wavelength dependence when the emission is broadband

spectroscopy · model-disagreement · readiness 4 · novelty 3

C32 — The measurement of oxygen non-stoichiometry in oxides by thermogravimetry includes a buoyancy correction that drifts with gas composition

materials-chem · hidden-parameter · readiness 4 · novelty 2

C33 — The dielectric constant of a confined liquid is inferred from a capacitor that measures the series combination

physical-chem · boundary-condition · readiness 4 · novelty 3

C34 — NMR relaxation-derived pore-size distributions assume a surface relaxivity that is calibrated on a different mineralogy

geochem · extrapolation · readiness 4 · novelty 3

C35 — The electrochemically measured double-layer capacitance of a porous electrode follows a power law in frequency that is indistinguishable from a constant-phase element

electrochem · model-artifact · readiness 4 · novelty 3

C36 — The measured enthalpy of adsorption from isotherms depends on the isotherm model because the model fixes the saturation capacity

physical-chem · model-disagreement · readiness 4 · novelty 2

C37 — The measured Lewis basicity of an ionic liquid is a function of its water content, which is rarely measured

physical-chem · hidden-parameter · readiness 4 · novelty 3

C38 — Scanning electrochemical microscopy assigns a finite rate constant to insulating regions because its theory assumes a conductive substrate

electrochem · model-artifact · readiness 4 · novelty 3

C39 — The apparent cooperativity of a supramolecular host is an artefact of fitting a 1:1 model to a 1:2 system

supramolecular · model-artifact · readiness 5 · novelty 2

C40 — The thermal conductivity of a liquid from the transient hot-wire method is biased by natural convection that begins earlier than the standard criterion assumes

physical-chem · time-dependent · readiness 4 · novelty 3

C41 — The measured Seebeck coefficient of a thin film includes a contact thermopower that is of the same order as the film’s

materials-chem · boundary-condition · readiness 4 · novelty 3

C42 — The turnover frequency of a single-atom catalyst is computed per total metal atom, but most atoms are inactive

catalysis · hidden-parameter · readiness 4 · novelty 3

C43 — The measured viscosity of a confined fluid is dominated by the wall’s roughness, not by the fluid

physical-chem · boundary-condition · readiness 3 · novelty 3

C44 — The reported stability number of a metal–organic framework is set by the detection limit of the diffraction measurement

materials-chem · blind-spot · readiness 4 · novelty 3

C45 — The measured dielectric breakdown strength of a thin film is limited by the electrode’s edge field, not by the film

materials-chem · boundary-condition · readiness 4 · novelty 3

C46 — The apparent rate of a photochemical reaction in a flow reactor is set by the photon flux distribution, not by the catalyst

chem-eng · boundary-condition · readiness 4 · novelty 3

C47 — The measured hydrogen evolution overpotential on a single crystal depends on the surface’s reconstruction, which is set by the electrolyte’s cation

electrochem · hidden-parameter · readiness 3 · novelty 3

C48 — The quantification of trace metals by ICP-MS is biased by the sample matrix’s carbon content through charge transfer

analytical-chem · hidden-parameter · readiness 4 · novelty 2

C49 — The reported photostability half-life of a dye is set by the oxygen concentration in the cuvette

photochem · hidden-parameter · readiness 4 · novelty 3

C50 — The “intrinsic” catalytic activity from density-functional theory is compared with experiment through a free-energy diagram that omits configurational entropy of adsorbates

computational-chem · model-artifact · readiness 4 · novelty 3

Materials science — 50 hypotheses

Every entry is a proposition. No experiment below has been performed.

M01 — Reported in-plane thermal conductivity of a supported 2D film is a function of the laser spot size, and in the large-spot limit it measures the substrate conductance instead

materials · boundary-condition · readiness 4 · novelty 4

M02 — Thin-film electrical conductivity is not a material property when the pads are comparable in conductivity to the film

materials · boundary-condition · readiness 5 · novelty 2

M03 — Interface-dominated thermal boundary conductance measured by time-domain thermoreflectance is biased by the transducer’s own boundary

materials · boundary-condition · readiness 4 · novelty 3

M04 — Grain-boundary resistivity extracted from impedance spectra assumes a brickwork geometry whose exponent is fitted, not measured

materials · model-artifact · readiness 4 · novelty 3

M05 — The fracture toughness of a thin film measured by channel cracking includes a residual-stress term that is set by the deposition, not by the film

materials · hidden-parameter · readiness 4 · novelty 3

M06 — Nanoindentation hardness depends on the tip’s actual area function at small depths, and the calibration is performed on a material with a different modulus

materials · calibration · readiness 4 · novelty 3

M07 — The measured bandgap of a nanocrystal film includes a strain shift that tracks the ligand, not the size

materials · hidden-parameter · readiness 4 · novelty 3

M08 — Piezoresponse force microscopy reports ferroelectricity in materials that are only electromechanically active

materials · blind-spot · readiness 4 · novelty 3

M09 — The superconducting critical current of a coated conductor is limited by a current-transfer length that is not in the reported Jc

materials · boundary-condition · readiness 4 · novelty 3

M10 — The measured thermal expansion of a film on a substrate is the difference of two large numbers and inherits the substrate’s uncertainty

materials · model-disagreement · readiness 4 · novelty 2

M11 — The “intrinsic” mobility from a field-effect transistor includes contact resistance that is fitted, not measured

materials · circularity · readiness 4 · novelty 3

M12 — Cathodoluminescence quantum efficiency of a phosphor is measured under an excitation density that is orders of magnitude above the application’s

materials · nonlinearity · readiness 4 · novelty 3

M13 — The degradation rate of a photovoltaic absorber measured under one spectrum does not transfer to another because the damage is carrier-density-driven

materials · time-dependent · readiness 4 · novelty 3

M14 — The measured fracture strain of a metallic glass depends on the sample’s free volume, which is set by the quenching rate and is not reported

materials · hidden-parameter · readiness 4 · novelty 3

M15 — The measured magnetocaloric entropy change depends on the protocol’s field-sweep rate through a lag that is never corrected

materials · time-dependent · readiness 4 · novelty 2

M16 — Reported thermoelectric figure of merit is dominated by the uncertainty in the thermal diffusivity, and the two measurements are made on different specimens

materials · model-disagreement · readiness 4 · novelty 2

M17 — The measured corrosion potential of a coated metal is set by the coating’s pinholes, not by its barrier properties

materials · boundary-condition · readiness 4 · novelty 3

M18 — The measured Curie temperature of a thin film is shifted by the film’s own demagnetising field, and the shift depends on the patterning

materials · boundary-condition · readiness 4 · novelty 3

M19 — The measured ionic conductivity of a solid electrolyte in a symmetric cell includes an interfacial resistance that grows with time

materials · time-dependent · readiness 5 · novelty 3

M20 — The measured work function of a 2D material is contaminated by adsorbates whose coverage tracks the transfer process

materials · hidden-parameter · readiness 4 · novelty 3

M21 — The reported piezoelectric coefficient d₃₃ of a thin film includes a substrate-clamping factor evaluated at the wrong boundary condition

materials · boundary-condition · readiness 4 · novelty 3

M22 — The measured thermal stability of a phase-change material is a function of the capping layer, which is treated as inert

materials · boundary-condition · readiness 4 · novelty 3

M23 — The reported spin Hall angle is contaminated by the inverse spin galvanic effect in the same bilayer

materials · model-disagreement · readiness 3 · novelty 3

M24 — The measured thermal conductivity of a porous material by the transient plane source method includes a contact resistance that is a function of the applied pressure

materials · boundary-condition · readiness 4 · novelty 2

M25 — The measured optical bandgap of a mixed-halide perovskite is inhomogeneous, and the “gap” is a fit to a distribution

materials · model-artifact · readiness 4 · novelty 3

M26 — The measured hardness of a high-entropy alloy is reported for a phase that is not single

materials · model-artifact · readiness 4 · novelty 3

M27 — The measured dielectric loss of a low-loss material at microwave frequencies is dominated by the metal housing’s surface resistance

materials · boundary-condition · readiness 4 · novelty 3

M28 — The measured spin-wave lifetime in a thin film is limited by the film’s thickness variation, not by the damping

materials · hidden-parameter · readiness 4 · novelty 2

M29 — The measured fracture toughness of a ceramic composite is a rising R-curve value quoted as a single number

materials · boundary-condition · readiness 4 · novelty 2

M30 — The measured activation energy of grain-boundary diffusion from thin-film interdiffusion includes a surface-diffusion shortcut

materials · boundary-condition · readiness 4 · novelty 3

M31 — The measured contact angle of a liquid on a “smooth” surface is in the Cassie state without the measurement detecting it

materials · hidden-parameter · readiness 4 · novelty 3

M32 — The measured thermal conductivity of a polymer composite is dominated by the percolation state, which depends on processing and not on filler loading

materials · hidden-parameter · readiness 4 · novelty 2

M33 — The measured dielectric breakdown of a polymer film is an extrinsic Weibull distribution whose scale parameter is set by the electrode area

materials · boundary-condition · readiness 5 · novelty 2

M34 — The measured electrochemical window of a solid electrolyte is a kinetic window whose width depends on the scan rate

materials · time-dependent · readiness 5 · novelty 3

M35 — The measured Seebeck coefficient of a composite is a percolation-weighted average that cannot be predicted from the constituents’ Seebeck coefficients alone

materials · model-disagreement · readiness 4 · novelty 3

M36 — The measured ion migration activation energy in a halide perovskite depends on the electrode’s Fermi-level pinning

materials · boundary-condition · readiness 3 · novelty 3

M37 — The measured radiation tolerance of a material is set by the test’s dose rate through dynamic annealing

materials · time-dependent · readiness 4 · novelty 3

M38 — The measured thermal boundary conductance of a metal–dielectric interface is dominated by the metal’s electron–phonon coupling length, not by the interface

materials · hidden-parameter · readiness 4 · novelty 3

M39 — The measured photostriction of a ferroelectric is mostly a thermal effect that the control experiment cannot subtract

materials · model-disagreement · readiness 4 · novelty 3

M40 — The measured “self-healing” efficiency of a polymer is a function of the test’s waiting time

materials · time-dependent · readiness 5 · novelty 2

M41 — The measured superconducting penetration depth in a thin film includes the film’s finite thickness through a geometric factor that is often neglected

materials · boundary-condition · readiness 4 · novelty 3

M42 — The measured catalytic activity of a surface is reported for a reconstruction that the reaction itself induces

materials · circularity · readiness 3 · novelty 3

M43 — The measured ionic conductivity enhancement in a nanocomposite is an artefact of the second phase’s electronic leakage

materials · model-artifact · readiness 4 · novelty 3

M44 — The measured magnetic anisotropy of a thin film is dominated by the seed layer’s texture

materials · hidden-parameter · readiness 4 · novelty 2

M45 — The measured thermal conductivity of an amorphous film is reduced by the film’s surface, and the reduction scales with thickness

materials · boundary-condition · readiness 4 · novelty 3

M46 — The measured photoluminescence blinking statistics of a quantum dot are set by the integration time, not by the emitter

materials · time-dependent · readiness 4 · novelty 3

M47 — The measured residual stress in a coating by X-ray diffraction assumes a stress-free lattice spacing that is not measured

materials · assumption · readiness 5 · novelty 2

M48 — The measured electrocaloric temperature change depends on the field’s waveform, and the literature reports values at different waveforms

materials · time-dependent · readiness 4 · novelty 3

M49 — The measured carrier lifetime in a semiconductor is limited by surface recombination whose velocity changes with the passivation’s aging

materials · time-dependent · readiness 4 · novelty 2

M50 — The measured figure of merit of a thermoelectric module and of its material differ because the module’s contact resistance is assigned to the material

materials · boundary-condition · readiness 5 · novelty 3

Biology and medicine — 50 hypotheses

Every entry is a proposition. No experiment below has been performed.

B01 — Optical-density growth curves saturate before the reader says they do, and every fitted growth rate is compressed by the same detector nonlinearity

microbiology · nonlinearity · readiness 5 · novelty 3

B02 — Quantitative PCR efficiencies are estimated from a dilution series that is itself biased by the dilution’s pipetting error

molecular-biology · circularity · readiness 4 · novelty 3

B03 — Western blot band intensities are in the saturated regime more often than reported, and the saturation is antibody-dependent

molecular-biology · nonlinearity · readiness 5 · novelty 2

B04 — Single-cell RNA-seq “dropout” is partly a capture-rate artefact that depends on cell size, so pseudotime trajectories are size-biased

transcriptomics · hidden-parameter · readiness 4 · novelty 3

B05 — Cryo-EM particle picking is confirmation-biased, and the bias grows with the strength of the prior

structural-biology · selection · readiness 4 · novelty 3

B06 — Calcium imaging’s inferred spike rate depends on the indicator’s binding kinetics in a way that mimics network state changes

neuroscience · model-disagreement · readiness 4 · novelty 3

B07 — The apparent allometric exponent of metabolic rate depends on the measurement temperature’s deviation from the species’ preferred range

ecology · model-artifact · readiness 3 · novelty 3

B08 — Patch-clamp series-resistance compensation distorts the very kinetics it is used to measure

electrophysiology · boundary-condition · readiness 4 · novelty 3

B09 — Flow-cytometry compensation matrices are fitted on single-stained controls whose autofluorescence differs from the experimental sample’s

cytometry · calibration · readiness 4 · novelty 3

B10 — The measured maximum oxygen consumption rate in respirometry is limited by oxygen diffusion into the chamber, not by the tissue

bioenergetics · boundary-condition · readiness 4 · novelty 3

B11 — The inferred selectivity of an antimicrobial peptide depends on the assay’s ionic strength through a membrane-binding term

microbiology · hidden-parameter · readiness 4 · novelty 3

B12 — The apparent heterogeneity of a bacterial population is an artefact of the plate reader’s well-to-well thermal gradient

microbiology · boundary-condition · readiness 4 · novelty 3

B13 — The measured protein half-life from cycloheximide chase includes a translation-independent decay that starts before the chase

cell-biology · time-dependent · readiness 4 · novelty 3

B14 — The inferred microbiome composition from 16S sequencing is set by the extraction kit’s lysis bias, which correlates with the phenotype being studied

microbiome · hidden-parameter · readiness 4 · novelty 3

B15 — The measured enzyme velocity in a plate assay includes a substrate depletion term that is invisible at the standard time point

biochemistry · time-dependent · readiness 5 · novelty 2

B16 — The measured binding affinity from surface plasmon resonance is limited by mass transport, and the limitation is hidden by a good global fit

biophysics · boundary-condition · readiness 4 · novelty 3

B17 — The measured membrane potential from a fluorescent dye is a weighted average dominated by the dye’s partitioning, not by the voltage

cell-biology · model-artifact · readiness 4 · novelty 3

B18 — The measured reactive-oxygen signal is dominated by the probe’s own photo-generated species

cell-biology · nonlinearity · readiness 4 · novelty 3

B19 — The measured ATP level from a luciferase assay depends on the lysis time because ATP is consumed during extraction

biochemistry · time-dependent · readiness 4 · novelty 2

B20 — The measured cytotoxicity of a nanoparticle includes an interference term between the particle and the assay dye

toxicology · model-artifact · readiness 5 · novelty 2

B21 — The measured wound-healing rate in a scratch assay is dominated by cell proliferation at the edges, not by migration

cell-biology · model-disagreement · readiness 4 · novelty 2

B22 — The measured affinity of an antibody in ELISA is limited by the hook effect, which suppresses signal at high concentration without warning

immunoassay · nonlinearity · readiness 5 · novelty 2

B23 — The measured transcription rate from nascent-RNA sequencing depends on the labelling time relative to the elongation rate

transcriptomics · time-dependent · readiness 4 · novelty 3

B24 — The measured microbiota-mediated drug metabolism depends on the oxygen gradient in the culture, which is not controlled

microbiome · boundary-condition · readiness 4 · novelty 3

B25 — The measured circadian period from bioluminescence recordings is biased by the reporter’s maturation time

chronobiology · model-artifact · readiness 4 · novelty 3

B26 — The measured optogenetic activation depth profile assumes a scattering coefficient that is not measured in the tissue being stimulated

neuroscience · hidden-parameter · readiness 4 · novelty 3

B27 — The measured synaptic plasticity magnitude depends on the recording electrode’s position relative to the dendritic tree

neuroscience · boundary-condition · readiness 3 · novelty 3

B28 — The measured bacterial mutation rate from fluctuation tests depends on the plating delay

genetics · time-dependent · readiness 4 · novelty 3

B29 — The measured cell-cycle phase distribution from DNA content is distorted by the fixation’s chromatin compaction

cytometry · model-artifact · readiness 4 · novelty 2

B30 — The measured drug potency in a 2D monolayer does not transfer to 3D because the readout’s dynamic range changes, not the drug

pharmacology · model-disagreement · readiness 4 · novelty 3

B31 — The measured protein oligomerisation state from size-exclusion chromatography is set by the column’s residence time

biochemistry · time-dependent · readiness 4 · novelty 3

B32 — The measured antibiotic tolerance of a biofilm is dominated by the assay’s washing step

microbiology · model-artifact · readiness 4 · novelty 2

B33 — The measured gut transit time from dye markers is biased by the marker’s own effect on water absorption

physiology · hidden-parameter · readiness 3 · novelty 3

B34 — The measured immune-cell cytokine release depends on the plate’s surface treatment, which varies between manufacturers

immunology · boundary-condition · readiness 4 · novelty 3

B35 — The measured longevity effect of a dietary intervention is confounded by the control diet’s composition changing between batches

geroscience · hidden-parameter · readiness 3 · novelty 3

B36 — The measured photosynthetic rate from chlorophyll fluorescence is nonlinear in the light intensity used to probe it

plant-physiology · nonlinearity · readiness 4 · novelty 3

B37 — The measured species richness from eDNA is bounded by the primer’s mismatch tolerance, which is biased against the taxa of interest

ecology · blind-spot · readiness 4 · novelty 3

B38 — The measured thermal tolerance of an ectotherm depends on the acclimation rate, not only on the acclimation temperature

ecology · time-dependent · readiness 3 · novelty 3

B39 — The measured association between a biomarker and a disease is attenuated by the assay’s limit of detection in a way that depends on the case mix

epidemiology · selection · readiness 4 · novelty 3

B40 — The measured gut-brain effect of a probiotic is confounded by the capsule’s excipient, which is fermentable

microbiome · hidden-parameter · readiness 3 · novelty 3

B41 — The measured protein–protein interaction affinity from yeast two-hybrid is a function of the reporter’s dynamic range, not of the affinity

molecular-biology · nonlinearity · readiness 4 · novelty 3

B42 — The measured membrane permeability from Caco-2 assays depends on the insert’s unstirred water layer

pharmacology · boundary-condition · readiness 4 · novelty 3

B43 — The measured chromatin accessibility difference between conditions is driven by the sequencing depth’s interaction with peak calling

epigenomics · model-artifact · readiness 4 · novelty 3

B44 — The measured developmental timing of an organism is shifted by the temperature of the imaging stage

developmental-biology · time-dependent · readiness 4 · novelty 2

B45 — The measured mechanical stiffness of a tissue from AFM is dominated by the probe’s geometry at the scale of the cell

biophysics · boundary-condition · readiness 4 · novelty 3

B46 — The measured insect flight metabolic rate from CO₂ respirometry is biased by the chamber’s washout time

physiology · time-dependent · readiness 4 · novelty 2

B47 — The measured evolutionary rate from serial-passage experiments includes a selection term from the passage bottleneck

evolution · boundary-condition · readiness 4 · novelty 3

B48 — The measured vaccine immunogenicity in mice is confounded by the microbiome’s batch-dependent adjuvant effect

immunology · hidden-parameter · readiness 3 · novelty 3

B49 — The measured protein turnover from heavy-water labelling is biased by the precursor pool’s non-uniform enrichment

proteomics · model-artifact · readiness 4 · novelty 3

B50 — The measured efficacy of an antifungal in vivo is dominated by the compound’s binding to serum proteins, which varies between species

pharmacology · hidden-parameter · readiness 3 · novelty 3

Engineering, Earth and environmental science — 50 hypotheses

Every entry is a proposition. No experiment below has been performed.

E01 — Low-cost air-quality sensor networks report a bias that is a function of relative humidity and is absorbed into the calibration slope

environmental-engineering · hidden-parameter · readiness 5 · novelty 2

E02 — Strain-based structural health monitoring attributes temperature-driven strain to damage

civil-engineering · time-dependent · readiness 4 · novelty 3

E03 — Battery state-of-health estimates from impedance are degenerate with the cell’s compression state

energy-engineering · degeneracy · readiness 4 · novelty 3

E04 — Rain-gauge calibration is biased by wind-induced undercatch in a way that increases with gauge age

hydrology · boundary-condition · readiness 4 · novelty 2

geodesy · hidden-parameter · readiness 4 · novelty 3

E06 — Seismic magnitude estimates from surface waves saturate at the same amplitude as the recording channel, in a magnitude-dependent way

seismology · nonlinearity · readiness 4 · novelty 3

E07 — Radar rainfall estimates are biased by the drop-size distribution’s dependence on the storm’s lifecycle stage, not on its intensity

remote-sensing · model-disagreement · readiness 4 · novelty 3

E08 — The measured efficiency of a wind turbine is degraded by the nacelle anemometer’s position, which is in the rotor’s induction field

energy-engineering · boundary-condition · readiness 4 · novelty 3

E09 — The measured soiling loss of a photovoltaic plant is dominated by the cleaning protocol’s resuspension, not by deposition

energy-engineering · model-artifact · readiness 4 · novelty 2

E10 — Acoustic leak detection in pipes is confused by the pipe’s burial depth, which shifts the dispersion in a way that mimics a different leak size

engineering · model-disagreement · readiness 4 · novelty 3

E11 — The measured thermal comfort of a building is a function of the sensor’s radiant environment, not of the air temperature it reports

building-science · boundary-condition · readiness 4 · novelty 2

E12 — The measured capacity fade of a flow battery includes a crossover term that is a function of the pump’s duty cycle

energy-engineering · time-dependent · readiness 4 · novelty 3

E13 — The measured seismic site response is biased by the reference site’s own amplification

seismology · circularity · readiness 4 · novelty 3

E14 — The measured glacier mass balance from stake networks is biased by the stakes’ own effect on local melt

glaciology · boundary-condition · readiness 4 · novelty 3

E15 — The measured ozone trend from sondes is affected by the sensor’s pump efficiency, which degrades with age and with altitude

atmospheric-science · hidden-parameter · readiness 4 · novelty 3

E16 — The measured soil moisture from cosmic-ray neutron sensors depends on the vegetation’s biomass, which changes with the season

hydrology · hidden-parameter · readiness 4 · novelty 3

E17 — The measured aerodynamic roughness of a city from tower data depends on the tower’s own wake

atmospheric-science · boundary-condition · readiness 3 · novelty 3

E18 — The measured groundwater recharge from the water-table fluctuation method is biased by the specific yield’s dependence on the water table’s depth

hydrology · hidden-parameter · readiness 4 · novelty 3

E19 — The measured corrosion rate of buried pipeline steel from ER probes is dominated by the soil’s aeration cycle

engineering · time-dependent · readiness 4 · novelty 2

E20 — The measured fatigue life of a welded joint depends on the residual stress field, which the test specimen does not reproduce

mechanical-engineering · boundary-condition · readiness 4 · novelty 3

E21 — The measured performance of a heat exchanger is degraded by fouling that the test protocol itself induces on the first run

thermal-engineering · time-dependent · readiness 4 · novelty 2

E22 — The measured efficiency of an electrolyser is biased by the bubble layer, and the bias depends on the current density’s history

energy-engineering · nonlinearity · readiness 4 · novelty 3

E23 — Train delay propagation is measured with a threshold that removes the very events that carry the amplification

transport-engineering · selection · readiness 4 · novelty 3

E24 — The measured comfort of an indoor environment is confounded by the survey’s own recruitment, which selects people who are uncomfortable

building-science · selection · readiness 3 · novelty 3

E25 — The measured durability of a concrete from accelerated carbonation is not transferable because the accelerating CO₂ concentration changes the reaction product

civil-engineering · model-disagreement · readiness 4 · novelty 3

E26 — The measured noise of a MEMS accelerometer includes a bias-drift term that is a function of the package’s thermal gradient, not of the sensor

instrumentation · hidden-parameter · readiness 4 · novelty 3

E27 — The measured sound insulation of a partition depends on the receiving room’s absorption, which is not reported

acoustics · boundary-condition · readiness 5 · novelty 2

E28 — The measured state of charge of a lithium cell from open-circuit voltage requires a relaxation time that is longer than most protocols allow

energy-engineering · time-dependent · readiness 5 · novelty 3

E29 — The measured fire resistance of a composite is dominated by the test furnace’s oxygen availability

fire-engineering · boundary-condition · readiness 4 · novelty 3

E30 — The measured particle emission of a brake depends on the dynamometer’s cooling airflow, which dilutes and ages the aerosol

environmental-engineering · boundary-condition · readiness 4 · novelty 3

E31 — The measured thermal conductivity of an insulation is reported for a specimen thickness that suppresses convection

building-science · boundary-condition · readiness 4 · novelty 2

E32 — The measured thermal performance of a battery pack is dominated by contact resistance that varies with the cell’s swelling over life

energy-engineering · hidden-parameter · readiness 4 · novelty 3

E33 — The measured vibration serviceability of a floor is biased by the test’s excitation method, which is not the excitation in service

civil-engineering · model-disagreement · readiness 4 · novelty 3

E34 — The measured efficiency of a thermoelectric generator in a system test includes a parasitic that is attributed to the material

energy-engineering · model-artifact · readiness 4 · novelty 3

E35 — The measured aerosol optical depth from a sun photometer is affected by the instrument’s temperature dependence in a way that mimics a diurnal cycle

atmospheric-science · hidden-parameter · readiness 4 · novelty 3

E36 — The measured urban heat island from satellite skin temperature is biased by the surface’s emissivity, which is not retrieved

remote-sensing · assumption · readiness 4 · novelty 3

E37 — The measured earthquake recurrence from paleoseismic trenches is biased by the trench’s detection threshold

geology · selection · readiness 3 · novelty 3

E38 — The measured heat flux from a geothermal well is biased by the circulation’s own thermal disturbance

geophysics · time-dependent · readiness 4 · novelty 2

E39 — The measured scour depth around a bridge pier from a single survey is a snapshot of a process with hysteresis

civil-engineering · time-dependent · readiness 3 · novelty 3

E40 — The measured thermal comfort of a naturally ventilated building depends on the wind pressure coefficient, which is assumed, not measured

building-science · hidden-parameter · readiness 4 · novelty 3

E41 — The measured thermal runaway onset of a cell depends on the calorimeter’s crucible, not on the cell chemistry

energy-engineering · boundary-condition · readiness 4 · novelty 2

E42 — The measured sediment oxygen demand in a lake is biased by the chamber’s stirring, which sets the diffusive boundary layer

limnology · boundary-condition · readiness 4 · novelty 3

E43 — The measured methane emission from a landfill by the tracer-release method is biased by the release height relative to the source

environmental-engineering · boundary-condition · readiness 3 · novelty 3

E44 — The measured bearing capacity of a pile from a load test includes a setup effect that is a function of the soil’s thixotropy

geotechnical · time-dependent · readiness 4 · novelty 3

E45 — The measured air-change rate of a building from a blower-door test is not the in-service rate, because the test changes the pressure field it measures

building-science · boundary-condition · readiness 5 · novelty 3

E46 — The measured extreme rainfall trend depends on the record’s averaging interval, which changed with automation

hydrology · model-disagreement · readiness 4 · novelty 3

E47 — The measured thermal conductivity of a soil from a probe is biased by the probe’s contact resistance, which changes with drying

geotechnical · boundary-condition · readiness 4 · novelty 3

E48 — The measured noise exposure from a wearable dosimeter is biased by the body’s acoustic shadow

occupational-health · boundary-condition · readiness 4 · novelty 2

E49 — The measured thermal performance of a solar collector is reported at a flow rate that is not the operating one

energy-engineering · boundary-condition · readiness 4 · novelty 2

E50 — The measured seismic vulnerability of a building stock is biased by the inspection’s targeting, which selects visibly damaged buildings

earthquake-engineering · selection · readiness 3 · novelty 3

Cross-cutting methodology — 50 hypotheses

These concern assumptions that are shared across the natural sciences, and the measurement artefacts they produce. Every entry is a proposition. No experiment below has been performed.

X01 — Finite-window decay exponents are properties of the window, and the offset is identifiable from curvature

methodology · identifiability · readiness 5 · novelty 4

X02 — Regression dilution biases every calibration curve fitted to a diluted standard series

methodology · errors-in-variables · readiness 5 · novelty 2

X03 — Spectroscopic baselines fitted over a fixed window absorb real bands and bias the peak parameters

methodology · model-artifact · readiness 5 · novelty 3

X04 — Aliasing of a slow drift into a fast periodic signal manufactures a resonance that is not in the system

methodology · time-dependent · readiness 4 · novelty 3

X05 — Instrument response deconvolution amplifies noise in a way that creates spurious fast components

methodology · ill-posed · readiness 4 · novelty 3

X06 — Model averaging over a discrete set of hypotheses produces confidence intervals that are too narrow when the set is incomplete

methodology · model-artifact · readiness 4 · novelty 3

X07 — Cross-validation on data that were preprocessed before splitting leaks information and inflates reported skill

methodology · circularity · readiness 5 · novelty 2

X08 — Rounding and digitisation of published values create apparent structure in meta-analysis

methodology · artefact · readiness 5 · novelty 3

X09 — Normalising to a reference sample imports that sample’s error into every subsequent measurement

methodology · hidden-parameter · readiness 5 · novelty 2

X10 — Compositional data analysed with standard statistics produce correlations that are forced by the closure constraint

methodology · artefact · readiness 5 · novelty 2

methodology · selection · readiness 4 · novelty 3

X12 — Two laboratories measuring the same quantity with the same method disagree because of a shared systematic that neither can see

methodology · model-disagreement · readiness 4 · novelty 3

X13 — Non-stationarity makes any estimated autocorrelation time too short, and hence every error bar too small

methodology · time-dependent · readiness 5 · novelty 3

X14 — A statistically significant difference between two noisy measurements is not evidence that they measure different things

methodology · inference · readiness 5 · novelty 2

methodology · model-artifact · readiness 5 · novelty 3

X16 — Smoothing before differentiating manufactures the feature that the derivative is used to locate

methodology · ill-posed · readiness 5 · novelty 2

X17 — Error bars from repeated measurements under-reproduce the true error because repetition shares the systematic

methodology · hidden-parameter · readiness 4 · novelty 3

X18 — Subsampling to balance a dataset discards the very regime where the model fails

methodology · selection · readiness 4 · novelty 3

X19 — Extrapolating a fitted trend beyond the calibration range is undetectable from the fit quality alone

methodology · extrapolation · readiness 4 · novelty 3

X20 — Consensus values from discrepant measurements depend on the weighting scheme more than on the data

methodology · model-disagreement · readiness 5 · novelty 3

X21 — Detrending with a fixed polynomial order removes a real low-frequency component and leaves a residual that looks like noise

methodology · model-artifact · readiness 4 · novelty 2

X22 — Averaging spectra before fitting changes the fitted parameters nonlinearly

methodology · nonlinearity · readiness 4 · novelty 3

X23 — Instrument linearity is verified over a range that excludes the operating point

methodology · blind-spot · readiness 5 · novelty 2

X24 — Anomalies detected by residual analysis are conditioned on the model that produced the residuals

methodology · circularity · readiness 4 · novelty 3

X25 — Two datasets that agree within their error bars can still be inconsistent when the errors are correlated

methodology · inference · readiness 4 · novelty 3

X26 — Interpolation between calibration points creates structure at the scale of the spacing

methodology · artefact · readiness 4 · novelty 2

X27 — Selecting the number of components by the scree plot is equivalent to thresholding noise at an arbitrary level

methodology · arbitrary-choice · readiness 4 · novelty 2

X28 — Correcting for a nuisance variable that is measured with error introduces more bias than it removes

methodology · errors-in-variables · readiness 4 · novelty 3

X29 — Peak-picking software’s default parameters encode a prior on peak width that becomes the reported result

methodology · model-artifact · readiness 5 · novelty 2

X30 — Physical constants extracted from a global fit absorb the fit’s unmodelled physics and appear anomalously precise

methodology · model-artifact · readiness 4 · novelty 3

X31 — Uncertainty propagation through a nonlinear forward model is asymmetric, so the quoted symmetric error bar is wrong at the precision claimed

methodology · nonlinearity · readiness 4 · novelty 3

X32 — Data-driven background estimates are trained on the signal region’s sidebands, which the signal contaminates

methodology · circularity · readiness 4 · novelty 3

X33 — Statistically optimal weighting is biased when the uncertainties are estimated from the same data

methodology · circularity · readiness 4 · novelty 3

X34 — Reproducibility failures in a field are concentrated in quantities whose uncertainty is dominated by a single unmeasured nuisance parameter

methodology · hidden-parameter · readiness 3 · novelty 3

X35 — Selecting a representative sample by its measured values makes the sample unrepresentative of the population it is meant to represent

methodology · selection · readiness 4 · novelty 3

X36 — Reanalysing published summary statistics cannot recover the effect that the original analysis reported when the original model was nonlinear

methodology · identifiability · readiness 4 · novelty 3

X37 — A null result from an underpowered experiment is not evidence of absence, and its inclusion in a meta-analysis biases the pooled effect

methodology · selection · readiness 5 · novelty 2

X38 — Calibration transfer between instruments assumes a linear mapping that fails precisely where the instruments differ most

methodology · model-disagreement · readiness 4 · novelty 3

X39 — Excluding “failed” runs on the basis of a quality metric that depends on the treatment creates the treatment effect

methodology · collider · readiness 4 · novelty 3

X40 — Sampling at a fixed interval synchronised to a periodic driver aliases the response to DC

methodology · aliasing · readiness 4 · novelty 3

X41 — Prior elicitation from expert opinion encodes the experts’ shared training, so the prior is tighter than the knowledge

methodology · hidden-parameter · readiness 3 · novelty 3

X42 — Reporting the best of several analysis choices is a selection effect that no correction in the paper can undo

methodology · selection · readiness 4 · novelty 3

X43 — A detection threshold calibrated on simulations inherits the simulation’s physics, so the threshold is a property of the simulator

methodology · circularity · readiness 4 · novelty 3

X44 — Combining measurements with a common systematic double-counts it when the correlation is assumed zero and under-counts when assumed one

methodology · model-artifact · readiness 4 · novelty 3

X45 — Time-averaging a nonlinear response function does not commute with averaging the input

methodology · nonlinearity · readiness 5 · novelty 3

X46 — Sparse sampling of a threshold crossing biases the estimated crossing time toward the sampling grid

methodology · artefact · readiness 4 · novelty 2

X47 — Normalising by a denominator measured with error creates a spurious negative correlation between ratio and denominator

methodology · artefact · readiness 5 · novelty 2

X48 — Quoting a detection limit from the blank’s standard deviation assumes the blank is representative of the sample matrix

methodology · hidden-parameter · readiness 5 · novelty 2

X49 — A monotonic but nonlinear sensor response makes any two-point calibration exact only at the points

methodology · nonlinearity · readiness 5 · novelty 2

X50 — The assumption that a measured quantity is extensive fails at the nanoscale, and molar quantities are reported anyway

methodology · boundary-condition · readiness 4 · novelty 3

Part IV — Method

What was built

  1. A source base. A programmatic harvest of 817 arXiv records submitted between January 2024 and December 2026, drawn from 49 queries aimed at measurement systematics rather than at subject matter: “systematic error”, “measurement bias”, “unobservable”, “blind spot”, “cannot be distinguished”, “degeneracy”, “identifiability”, “hidden variable”, “nuisance parameter”, “model discrepancy”, “interlaboratory”, “boundary condition”, “contact resistance”, “nonlinear impedance”, “third harmonic”, “small-signal approximation”, “Kramers–Kronig”, “instrument response”, “deconvolution”, “drift”, “aging”, “hysteresis”, “model misspecification”, and 26 others. The harvester is src/harvest_arxiv.py; the raw pack is data/arxiv_pack.json.
  2. A prior-art screen. 358 unique prior Incoprea hypothesis titles were extracted from the existing export bundles, and every new title was compared against them by string similarity. Two substantive overlaps were found and replaced (see CORRECTIONS.md).
  3. Hypothesis construction. 300 hypotheses were written directly, in six domain batches: physics and astronomy (50), chemistry and electrochemistry (50), materials (50), biology and medicine (50), engineering and Earth science (50), cross-cutting methodology (50). Each was required to have a named baseline, a mechanism, a discriminating observation, an available test, prior art, and an explicit refutation. The parser src/parse_hyp.py enforces the schema and rejects missing fields.
  4. Selection and refinement. 30 were selected for development on three criteria: the mechanism had to be expressible quantitatively; the blind spot had to be invisible to the instrument or test that is normally used as a check; and the refutation had to be cheap. Refinement required labelling each part of the claim as an identity, an artefact, or a genuine prediction.
  5. Investigation. Three were taken to full mathematical treatment with validated code: finite-window decay identifiability (I1), spot-size bias in thermal metrology (I2), and Kramers–Kronig blindness (I3). Every number quoted in the refined set is regenerated by investigations/R1_refinement_numbers.py.

What “readiness” means

Score Meaning
5 A reanalysis of published data, or a two-point change to an existing measurement, would settle it
4 Existing public data or an existing apparatus can confirm or kill it
3 Needs a dedicated measurement campaign or a new analysis pipeline
2 Needs new instrumentation
1 Needs the idea made precise before it needs an experiment

Readiness is a judgement about cost, not importance. Of the 300: 45 are scored 5, 201 are scored 4, and 54 are scored 3.

What “novelty” means

Score Meaning
5 A mechanism not present in the literature as far as the source base shows, with a new observable
4 A known mechanism applied where it is not currently applied, with a quantitative prediction
3 A known mechanism given a specific, testable form in a new domain
2 A known effect quantified for a domain that has not quantified it
1 A restatement or a small extension

Novelty 4–5 is claimed for 61 hypotheses; the rest are mostly 3. This is deliberate: most real progress in measurement science comes from taking a known mechanism seriously in a place it has not been taken seriously, not from inventing a new mechanism.

The three labels used in the refined set

Limits

Reproducing the collection

cd blindspot-2026-11-01
../.venv-research/bin/python src/parse_hyp.py            # rebuild CSV/JSON, validate schema
../.venv-research/bin/python investigations/I1_offset_window_bias.py
../.venv-research/bin/python investigations/I2_boundary_bias.py
../.venv-research/bin/python investigations/I3_kk_blindspot.py
../.venv-research/bin/python investigations/R1_refinement_numbers.py
python3 build/build_doc.py                                # assemble and typeset

The arXiv harvest is not required to rebuild the document; data/arxiv_pack.json is included. Re-running src/harvest_arxiv.py will produce a different pack because arXiv grows, so the pack shipped here is the one this collection was built from.

Part V — Corrections and negative results

This file records everything in the collection that changed during construction, every claim that failed a quantitative check, and every place where a hypothesis was narrowed rather than defended. It is deliberately kept separate from the hypotheses so that a reader can see what the evidence did to the original idea.

1. Two hypotheses were replaced before publication

C38 (chemistry). The original entry claimed that electrochemical ammonia synthesis rates near the detection limit are dominated by ambient and membrane-derived contamination. A check against the prior Incoprea corpus found an existing hypothesis making essentially the same claim (“Most reported electrochemical ammonia synthesis is contamination”). Rather than republish it with a new number, C38 was replaced with a different electrochemistry hypothesis: that scanning electrochemical microscopy assigns a finite rate constant to insulating regions because its feedback theory assumes a conductive substrate. The replacement has a different mechanism (diffusion-limited approach curve fitted with a conducting-substrate model), a different observable (tip-radius dependence of the apparent rate over a known insulator), and a different refutation.

P20 (physics). The original entry attributed the residual muon g−2 discrepancy to a scheme mismatch in the intermediate window between lattice and data. A prior Incoprea hypothesis already assigns the residual to lattice hadronic-vacuum-polarization systematics. The overlap was judged too close. P20 was replaced with a different precision-physics hypothesis: that optical-clock comparisons inherit an unmodelled self-gravity term from the apparatus mass. The replacement is testable with a ballast-variation experiment and does not depend on the g−2 literature.

2. A hypothesis failed its own quantitative check: R04 / B01

Original claim. Plate-reader OD600 compresses above ~0.3–0.6 because of detector saturation and stray light, suppressing fitted growth rates.

What was computed. A stray-light model, measured OD = −log₁₀(10^(−OD_true) + S), with the bias in fitted μ obtained from a log–log regression over four candidate windows (R1_refinement_numbers.py, section A).

Result. - S = 10⁻³, window OD 0.2–1.0: bias −0.1% - S = 10⁻², window OD 0.2–1.0: bias −1.1% - S = 10⁻³, window OD 2.0–3.0: bias −8.0% - S = 10⁻², window OD 2.0–3.0: bias −23.4%

Conclusion. Stray light cannot explain compression in the OD 0.3–0.6 range. The hypothesis as originally stated is not supported. It was narrowed: the mechanism is real but confined to OD > 1.5, and any sub-exponential growth below OD 1 must have a different cause. The entry in hyp/04-biology.md now carries the corrected numbers and names the surviving candidate mechanisms (detector nonlinearity, meniscus and fill volume, evaporation, physiological shift) along with the tests that separate them.

Why it is kept. A hypothesis that loses cleanly is the point of the collection. The failed mechanism was removed from the suspect list for the low-OD regime, which is a real gain.

3. A hypothesis was corrected in direction but not in kind: R21 / X33

Original claim. Inverse-variance weighting with variances estimated from the same data biases the weighted mean toward points whose noise fluctuated low.

What was computed. 40 000 Monte Carlo trials with four measurements and 2–30 degrees of freedom per variance estimate.

Result. The mean is unbiased (−0.000 to 0.005). The spread of the estimator exceeds its nominal value: 0.686 at 2 dof, 0.582 at 5, 0.539 at 10, 0.511 at 30, against a nominal 0.5. The quoted uncertainty is therefore 73%, 86%, 93% and 98% of the true spread.

Conclusion. The heading was wrong, the phenomenon is real. The refined entry now claims uncertainty understatement rather than mean bias, with the dof-dependent magnitude.

4. A hypothesis overstated its own effect size: R20 / X13

Original claim. Non-stationarity makes every estimated autocorrelation time too short, and hence every error bar too small, by a large factor.

What was computed. For a linear trend of amplitude a against noise σ, the ratio of the true standard error to the naive one is √(a²/12 + σ²)/σ.

Result. 1.01 at a/σ = 0.5; 1.04 at 1; 1.15 at 2; 1.53 at 4.

Conclusion. The effect is real but modest — under a factor of two even when the trend is four times the noise. The refined entry says so explicitly and restricts the claim to regimes where the trend dominates.

5. A claim about test power was softened after computation

In I1 the initial framing assumed that a broad distribution of relaxation times would be indistinguishable from a power law over a short window. Direct evaluation of the log-normal Laplace transform showed the opposite: a log-normal spectrum produces a strongly curved decay, and a 0.5-decade window is enough to reject a single power law at 1% noise when the window sits on the spectral knee. The investigation was rebuilt around the offset term instead, where the degeneracy is genuine and the Cramér–Rao bound actually diverges. The discarded framing is recorded here rather than deleted.

6. Numerical errors caught during development

7. Things that were not done