Scenario Controls
Interpretation: This demo illustrates how behavioural and workflow proxies can be aggregated to infer cognitive load drift. In production, OCaLDE is governed as a structural diagnostic (non-punitive), with de-identified reporting by default.
Cognitive Load Curve
Behavioural Drift
Risk Projection
Root Cause Map
Load index over time —
Burnout risk
Optimal zone
Brownout risk
Organisational load (mean)
—
Aggregate cognitive load index (case-mix adjusted proxy).
Load variance
—
High variance suggests misallocation: some overloaded, others underloaded.
Persistence
—
How sustained the current zone is across the selected window.
Thresholds shown are illustrative. In production, thresholds are calibrated to N-of-1 baselines and interpreted through governance guardrails.
Behavioural drift signals
Decision latency drift
—
Shift in latency distribution vs baseline (proxy). Overload often increases tail latency or forces speed-up heuristics.
Diagnostic breadth
—
Compression suggests heuristic narrowing; expansion may reflect uncertainty under strain.
Escalation compression
—
Changes in escalation threshold (referral/imaging/admission proxy).
Risk projection
Burnout probability (7d)
—
Probability of sustained overload if current conditions persist (proxy).
Brownout probability (7d)
—
Probability of sustained underload / disengagement state (proxy).
Structural risk score
—
Composite of mean load, variance, persistence, and drift acceleration (proxy).
Root cause attribution (candidate map)
Staffing / rota architecture
—
Misalignment between demand and staffing cover (proxy).
Interruptions / context switching
—
High interruption density increases cognitive switching cost.
Administrative burden
—
Non-clinical load displacing clinical cognition.