voiage.methods.evidence_obsolescence_refresh.value_of_evidence_obsolescence_refresh

value_of_evidence_obsolescence_refresh

value_of_evidence_obsolescence_refresh([positional or keyword] evidence_values: np.ndarray | list[float] = None, [positional or keyword] evidence_age_months: np.ndarray | list[float] = None, [positional or keyword] half_lives_months: np.ndarray | list[float] = None, [positional or keyword] obsolescence_risks: np.ndarray | list[float] = None, [positional or keyword] refresh_costs: np.ndarray | list[float] = None, [positional or keyword] living_review_values: np.ndarray | list[float] = None, [positional or keyword] model_refresh_values: np.ndarray | list[float] = None, [positional or keyword] drift_rates: np.ndarray | list[float] = None, [keyword-only] refresh_threshold: float = 0.5, [keyword-only] refresh_cadence_months: float = 12.0) -> EvidenceObsolescenceRefreshResult

Estimate value from refreshing aging or drifting evidence.

A source is selected when its obsolescence risk multiplied by its drift rate reaches refresh_threshold. The method remains fixture-backed pending longitudinal evidence data, binding parity, and promotion review.

Parameters:

• evidence_values np.ndarray | list[float]
• evidence_age_months np.ndarray | list[float]
• half_lives_months np.ndarray | list[float]
• obsolescence_risks np.ndarray | list[float]
• refresh_costs np.ndarray | list[float]
• living_review_values np.ndarray | list[float]
• model_refresh_values np.ndarray | list[float]
• drift_rates np.ndarray | list[float]
• refresh_threshold float (default: 0.5)
• refresh_cadence_months float (default: 12.0)

Returns: EvidenceObsolescenceRefreshResult