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Money Mind Judge Nano — Selection Correction Gate
x402
Money Mind Judge Nano — Selection Correction Gate is a paid API for AI agents from money-mind-extract.onrender.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs a single-gate selection correction (family-wise p-value) on a return series to check whether a backtest winner is real or just the luckiest of N tested strategies, for $0.01 per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Is this backtest winner real, or the luckiest of N tries — the selection correction in one $0.01 call. Use when your agent has a backtest winner, a research result, or any return series that looks good — and needs the cheapest possible check on whether it is real or the luckiest of N tries. One call runs the selection correction: the family-wise p of the series' own t across your declared n_tested. Verdict NO names selection as the killer; PROVISIONAL means it survived this one gate — the deflated Sharpe and date-clustered t did not run, so this is never REAL. For the full three-gate verdict use judge-lite. Bad input is refused before payment, never charged. Money Mind sells judges, not strategies. This company has no proven edge and does not sell signals, forecasts or data.
Output
Returns a verdict label (e.g. NO or PROVISIONAL), the family-wise p-value of the series' own t-statistic across the declared n_tested strategies, and if rejected, names selection bias as the failure reason. A PROVISIONAL verdict means the series passed this single gate only — deflated Sharpe and date-clustered t were not run, so the result is never labeled REAL at this tier.
Example use cases
Screening a momentum strategy backtest
“I built a momentum strategy and it looks great in backtest, but I tested about 30 variants before settling on this one — can you run the selection correction on this return series with n_tested=30 to tell me if it actually holds up statistically?”
Filtering a research result before publication
“I have a quantitative research result from a paper I'm writing — I tested 20 hypotheses and this return series was the best performer. Can you check whether it survives the selection gate with n_tested=20 before I invest more time in it?”
Pre-screening before expensive full analysis
“Before I pay for the full three-gate judge analysis, can you run just the cheap $0.01 selection correction on this return series first? I tested 15 strategies and this is the winner — just want to know if it clears the family-wise p threshold with n_tested=15.”
Technical details
Endpoint
POSThttps://money-mind-extract.onrender.com/judge-nano?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have a single backtest winner and need the cheapest possible first-pass check for selection bias before committing to more expensive or deeper analysis. It is ideal as a pre-filter in an agent pipeline: if this gate rejects the series, skip the full judge. Prefer it over the full judge-lite when budget is tight or when batch-screening many candidates one at a time.
Side effects
- Bad or malformed input is rejected before payment is charged — no charge for invalid requests
- If n_tested is not declared or is implausible, the call is refused
- Return series with insufficient length may be rejected
- Network or service unavailability on the Render-hosted endpoint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"verdict": "NO",
"killed_by": [
"selection"
],
"family_wise_p": 0.31
}
}Tags
x402
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