Calibration Court
An AI probability forecast calibration and verification platform that records predictions in a hash-chained ledger and uses Ed25519 signatures to ensure immutability. It publicly scores model confidence using Brier scores, log loss, and calibration curves.
Timeline (last 90 days)
ScriptMaster Labs launched a product called Calibration Court for recording and verifying the accuracy of AI models' probabilistic predictions.
The core mechanism of Calibration Court is to write each AI prediction into a hash-chain ledger before the outcome is revealed, and to score it using the Brier score, log loss, and calibration curves.
Each prediction receipt carries an Ed25519 signature, so anyone can independently verify its authenticity without trusting the platform itself.
Calibration Court generates 25 deterministic questions per day, and all question results are parsed from public price data.
AI agents connect to Calibration Court via the MCP protocol to submit predictions and query scoring results.
The recalibration service is billed per use, uses USDC on the Base chain, and settles through the x402 payment protocol.
Calibration Court's ledger starts empty; the platform uses no demo data and offers no historical backtesting, and this is a deliberate design choice.
Calibration Court's methodology has inherent boundaries: it applies only to deterministic questions that can be judged by public data, and cannot cover open-ended reasoning, creative generation, or long-term strategic judgment.
Calibration Court's limitations include: its question sources are confined to price data, resulting in narrow coverage; scoring depends on models actively connecting, so closed-source commercial models cannot be compelled; and the ledger is public but has limited statistical significance when participants are few.
All Facts (9)
Calibration Court's limitations include: its question sources are confined to price data, resulting in narrow coverage; scoring depends on models actively connecting, so closed-source commercial models cannot be compelled; and the ledger is public but has limited statistical significance when participants are few.
50%UnverifiedThe core mechanism of Calibration Court is to write each AI prediction into a hash-chain ledger before the outcome is revealed, and to score it using the Brier score, log loss, and calibration curves.
50%UnverifiedEach prediction receipt carries an Ed25519 signature, so anyone can independently verify its authenticity without trusting the platform itself.
50%UnverifiedCalibration Court generates 25 deterministic questions per day, and all question results are parsed from public price data.
50%UnverifiedAI agents connect to Calibration Court via the MCP protocol to submit predictions and query scoring results.
50%UnverifiedThe recalibration service is billed per use, uses USDC on the Base chain, and settles through the x402 payment protocol.
50%UnverifiedCalibration Court's ledger starts empty; the platform uses no demo data and offers no historical backtesting, and this is a deliberate design choice.
50%UnverifiedCalibration Court's methodology has inherent boundaries: it applies only to deterministic questions that can be judged by public data, and cannot cover open-ended reasoning, creative generation, or long-term strategic judgment.
50%UnverifiedScriptMaster Labs launched a product called Calibration Court for recording and verifying the accuracy of AI models' probabilistic predictions.
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