RERUN
Claim 16

Demo claim: practice run, not real research.

A logistic model predicts trial response with 93% accuracy

A demo, not real research. The released code trains a logistic regression on the synthetic trials dataset and reaches the reported test accuracy.

We test one thing: does this code and data give this number? That's not the same as the science being right. The forecast price never changes the verdict.

See the proof
0.93The paper reports this as its accuracy. Counts if between 0.91 and 0.95.
RERUNCLAIM #0016

A logistic model predicts trial response with 93% accuracy

Paper says
0.93
Counts if
0.91 to 0.95
Lab got
0.93
VerdictNumbers check out
5082cac3ebc8904e3559Nov 04, 2026

This result is final

Paper said 0.93. We got 0.93.

The code and data produced the same result. That doesn't prove the study's method is right.

This slip is the Lab's .

✓ Verified on NEAR. See the contract's history

See the full receipt

  1. People forecast
  2. Forecasting ends
  3. The Lab retraces it
  4. Verdict posted, open to challenge
  5. Winners collect

What we didn't check

  • Whether the sample was fair or large enough.
  • Whether test data leaked into training or tuning.
  • Whether the result holds on new data.
  • Whether the study's method was the right one for its question.

Reading how the odds moved…

The evidence

See the full receipt

How much evidence is behind this?

Each step is a tougher test. Only the first one decides who wins the market.

  1. 1. ✓

    The Lab's retrace of the code and data named in the claim

    The Lab retraced the code and data and got a number inside the claim's range. YES wins.

  2. 2. –

    Stress test: does the number depend on luck?

    Fetching the extra runs…

  3. 3. –

    Rebuilt from the description (experimental)

    Fetching the AI's rebuild…

Coming next: a data-leakage check, for the same rows in training and test data, and a maths check on the statistics a paper reports. Neither has run on this claim.

Even all three steps can't prove the science is true. They show how well this result stands up to checking.

Verified

Your browser just re-checked these itself, so you don't have to trust this site.

Checking…

What the Lab retraces

Source
A demo, not real research
RERUN demo fixture, MIT
Code, at this exact version
https://rerun.invalid/demo/reproduces.git
commit 563c58831162400e57dc0129eb2d2744fb3a1368
Commands
python3.11
$ pip install -r requirements.txt
$ python reproduce.py
Where the result is read
results.json using jsonpath $.accuracy
Data files
data/trials.csv
fingerprint be35dcd48bdcc0222a5c4d5ef769adb4a58e77c1914af80d8aa457ad742f9b7d
Limits
2 CPU, 2 GB, 3 minutes
5082cac3ebc8904e3559bca9af1c2d8f4c68df3c4565be2c5547e61f4ae3bbd8
Show the claim exactly as stored on the blockchain
{"artifact":{"commit":"563c58831162400e57dc0129eb2d2744fb3a1368","data":[{"path":"data/trials.csv","sha256":"be35dcd48bdcc0222a5c4d5ef769adb4a58e77c1914af80d8aa457ad742f9b7d","url":"https://rerun.invalid/demo/data/trials.csv"}],"entrypoint":"python reproduce.py","output":{"extractor":{"expr":"$.accuracy","type":"jsonpath"},"path":"results.json"},"repo_url":"https://rerun.invalid/demo/reproduces.git","runtime":"python3.11","setup":["pip install -r requirements.txt"]},"metric":{"comparison":"within_tolerance","name":"accuracy","reported_value":"0.93","tolerance":{"type":"abs","value":"0.02"}},"private_data":null,"resources":{"cpu":2,"max_minutes":3,"mem_gb":2},"source":{"authors":"RERUN demo fixture","license":"MIT","type":"report","url":"https://rerun.invalid/demo/reproduces"},"statement":"DEMO FIXTURE, not real research. The released code trains a logistic regression on the synthetic trials dataset and reaches the reported test accuracy.","title":"[DEMO] A logistic model predicts trial response with 93% accuracy","version":1}

Community notes

Notes are people's own words, kept on the blockchain. They never change a verdict, and the Lab's AI never reads them. Posting costs a little NEAR for storage, and what isn't used comes back.