Incoprea research · batch 1 index · 3 November 2026

Batch index and status

Index, methods and status for the 3 November batch. Every claim is listed with its measured spread or base rate and an explicit status. Four items are negative or failed; none is an experiment.

This is the index for the 3 November batch. Five pages, one computation set, no experiments.

1. Contents

PageSubjectHeadline
P1Dimensionless-law auditEight standard groups; spread at fixed value 1.13–125.89
P2Reversal base rates0% at two free coefficients, 24% at four
P3Constraint testsOne refutation, one synthetic power check, one construction failure
P4Theory notesInformal crossing bound; the spread criterion
P5Index (this page)Methods, status, reproduction, what to test next

2. Status of every claim in the batch

ClaimSpread / rateStatus
Pipe friction factor31.62model audit
Sphere drag coefficient1.94model audit
Channel conductance17.48model audit
Natural-convection Nusselt1.13model audit
Reactor conversion1.29model audit
Onset of Rayleigh-Benard convection2.60model audit
Laminar-turbulent transition1.96model audit
Diffusion coefficient125.89model audit
Response-time collapse2.74not supported
Membrane reversal, constrained0/4not supported
Crossing bound (S)0/600 violationsconsistent; not proved
Enzyme constrained test9.0×synthetic power check only
Fog drainage optimum1.00×construction failure

3. Methods

All computations are in one script, run_all.py, Python 3 with numpy only. Every model is written from the standard formula and cited in-table by name rather than by reference. Randomised procedures are seeded (default_rng(20261103)). Numbers in the pages are read from results/all_results.json; none is typed by hand.

Computations performed:

4. What this batch does not establish

5. What to do next, in order

  1. Automate the spread criterion. One function: given a law and two model variants, return the spread. Apply it to twenty laws.
  2. Prove or refute the S − 1 bound. This is a small mathematics problem with a clean statement.
  3. Code twenty published reversals for free-versus-measured coefficient counts. If the correlation holds, the screening rule is real.
  4. Fix the fog model with a non-monotone drainage term, or drop the hypothesis.
  5. Only then consider laboratory work — and only where a constrained model still predicts an effect.
If one sentence survives this batch: a model with a free coefficient will usually produce the effect you are looking for, and the count of free coefficients is the cheapest available estimate of how much of the result is the model rather than the world.

Status: computational model results, 3 November 2026. No experiment, no data, no measurement. No novelty claimed; no literature search performed. Code and raw JSON accompany this page set.