Research + Governance Framework

DT4H separates infrastructure modeling from clinical decision-making.

DT4H models cohorts, initializes Twins, computes calibration states, and supports downstream runtime systems. Clinical interpretation and operational execution remain separate responsibilities.

Governance diagram #

MODELDT4H

Cohorts · reference humans · Twin initialization · calibration

COMPUTEStateK

State · confidence · transition · readiness

EXECUTESETPOINT

Protocols · practices · feedback · outcomes

BOUNDARYGovernance

Clinical review · validation · oversight · claims control

Governance posture #

Infrastructure Role

What DT4H does

  • Constructs cohort-aware digital models.
  • Matches reference-human priors.
  • Initializes individualized Twins.
  • Tracks calibration and confidence.
  • Supports longitudinal state modeling.
  • Provides runtime intelligence infrastructure.
Boundary Conditions

What DT4H does not do

  • Does not independently diagnose disease.
  • Does not replace clinicians.
  • Does not prescribe treatment autonomously.
  • Does not claim validated medical outcomes.
  • Does not replace regulatory oversight.
  • Does not bypass human clinical interpretation.

Validation posture #

01

Separate hypotheses from claims

Research hypotheses must remain distinct from validated clinical claims.

02

Expose assumptions

Cohort and reference-human assumptions should remain inspectable.

03

Track confidence

Model maturity should be visible rather than implied.

04

Audit recalibration

Calibration updates should be traceable and explainable.

05

Preserve oversight

Clinical interpretation remains outside autonomous modeling systems.

06

Govern execution

SETPOINT execution should remain bounded by product and care governance.

Layer ownership #

DT4HModeling infrastructure

Owns cohorts, reference humans, Twin initialization, and calibration.

StateKState computation

Owns state, confidence, trajectory, and transition logic.

SETPOINTExecution runtime

Owns protocols, practices, outcomes, and feedback capture.

GovernanceInterpretation boundary

Owns clinical, research, compliance, and validation boundaries.

Implementation notes #

Keep governance visible

Clinical, research, and execution boundaries should be visible in product and platform workflows.

Separate validation stages

Hypothesis, prototype, research, pilot, and regulated deployment should remain distinct.

Audit boundary-sensitive outputs

Any output that could be interpreted clinically should carry confidence, provenance, and boundary language.

LayerGovernance Framework
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