CJTP Interactive Demo (Mocked) — Clinician Judgement Trajectory Predictor

Tracks a clinician’s judgement as a trajectory (learning, drift, decay). This file is standalone and uses simulated data only.

Controls

52
0.35
0.30
0.55
0.60
0.10
7

Interpretation: higher λ + better feedback tends to improve judgement; higher workload + higher δ increases decay risk. If this were real life, we would also model case-mix and outcome delay. The demo keeps it legible (and less judgemental).

Trajectory Charts

Latent Judgement State J(t) (higher is better)
Calibration Error Proxy (lower is better)
Discrimination Proxy (higher is better)
Decision Threshold Drift τ(t) (watch for sustained drift)