# Inference Under Uncertainty **Entity class:** Probabilistic And Inverse-Problem Layer concept **Inference Under Uncertainty** is an evidentiary control for representing limits, error, bias, or confidence rather than silently converting inference into fact. Used correctly, Inference Under Uncertainty supports conditional inference and collection planning without promoting proximity, exposure, or model output into proof. ## Counterterrorism predictive-graph role The page records capability and analytic function. Any claim of a named operational deployment remains subject to the [[wiki/Counterterrorism Predictive Graph Evidence Ladder|evidence ladder]]. The analytic state should distinguish ground truth, observed evidence, inferred state, and predicted state. ## Relationships - **domain router:** [[wiki/Bayesian Inference|Bayesian Inference]]. - **ontology neighbors:** [[wiki/Inference Under Partial Observation|Inference Under Partial Observation]] and [[wiki/Inverse Problem|Inverse Problem]]. - **synthesis:** [[wiki/Counterterrorism Predictive Graph|Counterterrorism Predictive Graph]] and [[wiki/Predictive Intelligence Loop|Predictive Intelligence Loop]]. ## Sources - [NIST/SEMATECH — e-Handbook of Statistical Methods (accessed September 23, 2026)](https://www.itl.nist.gov/div898/handbook/) - [Oden Institute — Tan Bui-Thanh research profile (accessed September 23, 2026)](https://oden.utexas.edu/people/directory/Tan-Bui/) **As of:** 2026-09-23