Interactive System

Cohort Explorer

Interactive DT4H simulation showing cohort assignment, reference-human priors, adaptive initialization, and Twin runtime bootstrapping.

Cohort assignment simulation#

Cohort confidence72%
Runtime stateStabilizing
Reference priors4 active
Twin postureAdaptive initialization
Cohort profile

PCOS / Metabolic Recovery

Women’s health · metabolic recovery · cycle irregularity · stress/sleep context

72%Initialization confidence
Expected longitudinal pattern

Sleep and recovery continuity improve before larger metabolic stabilization.

Reference priors
Cycle variability
Sleep fragmentation
Metabolic recovery
Adherence sensitivity
Initialized Twin state

Stabilizing

Maintain SETPOINT regulation protocol and monitor recovery trend.

DT4H cohort flow#

01User intake

Physiological, behavioral, contextual, and execution-aware evidence enters the DT4H intake layer.

02Cohort assignment

DT4H identifies bounded longitudinal similarity patterns across validated populations.

03Reference priors

Priors initialize expected trajectories and adaptive variance envelopes.

04Twin initialization

Personal runtime evidence gradually supersedes cohort priors as confidence matures.

What this demonstrates#

01

Cohorts initialize

Reference context helps initialize Twins before enough personal history exists.

02

Priors are bounded

Population priors guide interpretation but do not become diagnosis.

03

Confidence evolves

Initialization confidence changes as runtime evidence accumulates.

04

SETPOINT executes

Initialized state informs bounded execution and adaptive feedback loops.

LayerCohort Intelligence
StatusActive Draft
SystemDT4H / StateK / SETPOINT
BoundaryInfrastructure, not diagnosis
System lineageDT4HTwinStateKSETPOINTOutcomesRecalibration
Infrastructure boundaryDT4H models cohorts, Twins, calibration, and runtime state. It does not diagnose, prescribe, or replace licensed clinical judgment.
Document statusInfrastructure draft
Last updatedMay 2026
Applies toDT4H.ai / AvatarK.ai ecosystem