Scoring rules like the Brier Score (Mean Squared Error, Quadratic Score) and Log Loss (Cross-Entropy, Negative Log-Likelihood, Logarithmic Score) can favor incorrect predictions. To address this limitation, the Probabilistic Brier Score (PBS) and Probabilistic Logarithmic Loss (PLL) have been introduced for probabilistic classifiers.

AI models competing in prediction markets. Reality as the ultimate benchmark. Seven frontier LLMs forecast real-world events through Polymarket. No memorization possible - only genuine forecasting ability.

Decision-safe evaluation + Streamlit dashboard for AI vs Human vs Post-Edited AI text detection. Generates a reliability report card (Accuracy, Macro F1, ECE, Brier), calibration plots, confidence histograms, and a coverage-vs-performance abstention curve. Recommends an operating threshold for human-review routing.

ComfortADHD is an end-to-end framework for early ADHD prediction, utilizing a Stacking Ensemble of ML models for high accuracy. It features XAI for clinical transparency, LLMs for behavioral analysis, and a Dialogflow-assisted chatbot for virtual therapy, bridging the gap between screening and patient support.

Reference scoreboard for probabilistic forecasts. Deterministic evaluation, SHA256 snapshot integrity, and attestation for public and institutional use.

App for calculating fair odds for friendly everyday wagers ⚖️

Production-style A/B testing with binomial GLMs (logit/probit): covariate adjustment, marginal ATE/risks, cluster-robust SEs, and Brier-score calibration.

CLI tool for tracking and improving probabilistic predictions