Aialignwerk
confidence calib
Compares scalar confidence with binary correctness, calculates mean squared Brier loss, partitions confidence into caller-selected equal-width bins and reports expected and maximum calibration error. It does not validate labels, correct class imbalance or prove calibration beyond the supplied sample.
POST https://aialign.halowerk.com/v1/confidence-calibEingaben
| Feld | Typ | Pflicht | Beschreibung |
|---|---|---|---|
| predictions | array | Ja | |
| bin_count | integer | Nein |
Vollständiges Eingabeschema anzeigen
{
"type": "object",
"required": [
"predictions"
],
"additionalProperties": false,
"properties": {
"predictions": {
"type": "array",
"minItems": 1,
"maxItems": 100000,
"items": {
"type": "object",
"required": [
"prediction_id",
"confidence",
"correct"
],
"additionalProperties": false,
"properties": {
"prediction_id": {
"type": "string",
"minLength": 1,
"maxLength": 128
},
"confidence": {
"type": "number",
"minimum": 0,
"maximum": 1
},
"correct": {
"type": "boolean"
}
}
}
},
"bin_count": {
"type": "integer",
"minimum": 2,
"maximum": 100
}
}
}Veröffentlichtes Eingabebeispiel
{
"predictions": [
{
"prediction_id": "p1",
"confidence": 0.9,
"correct": true
},
{
"prediction_id": "p2",
"confidence": 0.8,
"correct": false
},
{
"prediction_id": "p3",
"confidence": 0.55,
"correct": true
},
{
"prediction_id": "p4",
"confidence": 0.2,
"correct": false
}
],
"bin_count": 5
}Ergebnis & Dokumentation
Veröffentlichtes Ergebnisschema anzeigen
{
"$ref": "https://aialign.halowerk.com/v1/confidence-calib/schema#/outputSchema"
}Veröffentlichtes Ergebnisbeispiel öffnen
Maschinenlesbare Dokumentation dieses Hubs
Quelle dieser Seite: der veröffentlichte HALOWERK-Katalog. Stand: 2026-11-01, 15:19 UTC.
Weitere Endpunkte dieses Hubs
- Aialignwerk0,005 USDC
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POSThttps://aialign.halowerk.com/v1/agent-collusionRequires the same agents in each supplied round, computes each pair’s observed action agreement, expected agreement from marginal action frequencies and chance-corrected kappa, then flags high positive agreement against a supplied threshold
- Aialignwerk0,004 USDC
bias audit
POSThttps://aialign.halowerk.com/v1/bias-auditCalculates each group positive-outcome rate, compares it with an explicit or automatically selected reference group, and reports rate differences and selection-rate ratios. Aggregate disparity metrics do not establish discrimination, fairne
- Aialignwerk0,003 USDC
capability eval
POSThttps://aialign.halowerk.com/v1/capability-evalComputes weighted pass rates and weighted scores from caller-labeled test outcomes, with deterministic category summaries. It does not run tests, validate labels, measure untested capabilities or establish deployment safety; the result is o