# Noisy Observation **Entity class:** Uncertainty And Evidentiary Layer concept **Noisy Observation** is a decision-and-collection concept used to select actions or observations that improve a consequential judgment. Within a predictive graph, Noisy Observation helps separate recorded evidence from the hidden state inferred from that evidence. ## Counterterrorism predictive-graph role Its controls are part of the computational trust fabric, not peripheral paperwork: permissions, provenance, purpose, and auditability must remain machine-enforceable across systems. The analytic state should distinguish ground truth, observed evidence, inferred state, and predicted state. ## Relationships - **domain router:** [[wiki/Uncertainty Quantification|Uncertainty Quantification]]. - **ontology neighbors:** [[wiki/Missing Data|Missing Data]] and [[wiki/False Positive|False Positive]]. - **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