[Lama9901]

What would change your mind? Genuine question.

The adversarial test is public and runnable in 5 minutes:

  git clone https://github.com/Lama999901/metagenesis-core-public
  python demos/open_data_demo_01/run_demo.py

If output isn't PASS/PASS on your machine, I want to know. If the protocol design is flawed, I want to know where specifically.

Known limitations are machine-readable: reports/known_faults.yaml

[Charon77]

First of all, I don't want to run anyone's code without proper explanation, so help me understand this. Let's start with the verifier. The 3rd party verifier receives a bundle, not knowing what the content is, not having access to the tool used to measure, and just run a single command based on the bundle which presumably contains expected results and actual measurements, both of which can easily be tampered. What good does that solve?

[Lama9901]

Right question. Bundle alone proves nothing — you're correct.

Two things make it non-trivial to fake:

The pipeline is public. You can read scripts/steward_audit.py before running anything. It's not a black box.

For materials claims — the expected value isn't in the bundle. Young's modulus for aluminium is ~70 GPa. Not my number. Physics. The verifier checks against that, not against something I provided.

ML and pipelines — provenance only, no physical grounding. Said so in known_faults.yaml :: SCOPE_001.

[wasabi991011]

If I may ask, how much of the code, original post, and comments are AI generated?

[Lama9901]

Heavily AI-assisted, not AI-generated.

Claude + Cursor wrote the structure. I fixed hundreds of errors — wrong tests, broken pipelines, docs that didn't match the code. That's literally why the verification layer exists. AI gets it wrong constantly.

This comment — also Claude, on my direction. That's the point. Tool, not author.

Clone it and run it. If it doesn't work, tell me.