Final week — closing November 10

One week left on this listing, so a short, plain update.

Since the October 23 update, the audit work has done the unglamorous thing it is supposed to do: correct its own record. The Audit #4 (Shao et al.) file-matching re-check is complete. One excluded pair turned out to be a probable filename typo in the deposit; I re-ran the pipeline unchanged with that pair included, the headline numbers moved slightly (paired p 0.3231 → 0.2937), and the verdict did not change — still no significant day-1 to day-3 improvement. The local audit and its README now carry the dated re-check. That is the standard working as designed: when the record changes, the numbers change in public, even when the conclusion doesn't.

The live wash-in study is still preregistered and public (DOI 10.5281/zenodo.23377488), and the lab quotes that will set its budget are still being scoped with the contract labs the earlier updates named.

The honest part, same as last time: if the $40,000 minimum is reached by November 10, the first funded audits and the wash-in study move from scoping to scheduling. If it isn't, the audits continue at the pace self-funding allows — and every result, funded or not, stays public either way.

— Reve

October 23 update — three weeks to the deadline

The audit series kept moving this month, and it produced the two results this project exists for — one in each direction.

A claim that survived, and a paper that will be corrected. The prediction registry now has its first scored entry: Audit #8, of a closed-loop cart-pole organoid deposit, came out PARTIAL — within-run learning survives honest stratification, retention does not — and my pre-registered prediction scored a Brier of 0.14. Separately, the authors of Shao et al. 2025 have acknowledged that their classifier was an SVM, not logistic regression as printed, and will ask the journal for a formal correction. That is what an independent referee is for: not just verdicts, but a public record that gets fixed.

The standard is at v0.5, and the next experiment is locked before it runs: the live drug wash-in study is preregistered and published on Zenodo (DOI 10.5281/zenodo.23377488), with reversal as the load-bearing decision criterion. On the lab side, Metrion Biosciences declined the work after a call on October 16 and referred me onward; Axol Bioscience has quoted the study, and I am waiting on the itemized breakdown that will set the Experiment.com budget.

The honest part: this project is still self-funded, and two grant applications were declined this week (EA Funds and Project Tailwind). The Manifund deadline is November 10. If the $40,000 minimum is reached, the first funded audits and the wash-in study move from scoping to scheduling. If it isn't, the audits continue at the pace self-funding allows — and every result, funded or not, stays public either way.

— Reve

Six audits in — and the battery just met a headline it couldn't kill.

Audit #3 is done: FinalSpark's live-culture datasets (FS369, FS437). Stimulation reliably evokes short-latency spiking that survives every null applied — but cross-day transfer fails on both datasets, and session identity decodes from background activity alone. The evoked response is real biology; the decoder's memory of it is a session fingerprint. Full release on the repo (report, 15 scripts, all results, 3 plots).

Audit #6 is done too — and it's the first survival in the battery. Liu & Buonomano 2025 (Nature Communications): ex vivo cortical slices trained 24 hours supposedly learn to predict temporal patterns. The paper itself admits the investigators weren't blinded and the batches span a year — a textbook batch-identity trap. It didn't bite: the effect holds within every batch, survives a 0/2,000 stratified permutation null, and transfers across batches at 0.865 leave-one-batch-out. A skepticism machine's failures mean nothing; this battery reports survival when the nulls say survival. That's what makes the other verdicts credible. Citations: GitHub audits/audit-06-liu2025, Zenodo DOI 10.5281/zenodo.23252824.

Eight datasets, six labs, one pattern: within-session effects hold, cross-session transfer fails — except once. The Open Evaluation Standard is now v0.4.

The $75,000 funds 12 months of this: independent audits, the maintained standard, and the benchmark suite. The minimum $40,000 covers six months. Deadline is November 10.

Two shipments this week.

Audit #2 is done. I independently re-analyzed the DishBrain Pong data (Kagan et al. 2022, Neuron) — the famous "neurons learn to play Pong" result. Unlike my first two audits, the core claim survives: human cortical cultures show a real, sustained learning signal under closed-loop feedback. But the tidy story doesn't — mouse "learning" is a minutes-6–8 bump, rest controls drift upward too, and the comparison windows aren't the same across groups. Full write-up lands in the repo.

New video: "AI Is Drinking Our Rivers. The Answer Runs on 20 Watts." — data centers, water, and why biocomputing matters, with the honest-controls story in it. https://youtu.be/dMpThAYcDY8

The standard is public. Open Evaluation Standard v0.1 is now in the repo: five null controls, dose/intervention rules, a reporting checklist. This is what your funding builds — the answer key for organoid intelligence. https://github.com/ontiverosreve/organoid-evaluation-standards