Decision Reassessment Under Restricted Evidence Access

Incremental inference, provenance and conservative decision rules can support reassessment when underlying evidence changes but cannot be disclosed in full. This paper proposes a combined protocol for advisory records using recipient-authorized impact bounds, explicit dependencies and auditable issuance states. The contribution is a testable integration specification and comparative evaluation plan, not new mathematics or a deployed capability. Synthetic fixtures check selected rule behavior; they do not establish intelligence accuracy or operational benefit. A proposed six-month feasibility study would compare cost, decision coverage, disclosure and analyst burden against equally informed conventional implementations. No comparative pilot, government deployment, security accreditation, operational validation or quantum advantage is reported. Independent decision-science, security, legal, privacy and human-factors review remains necessary. ChatGPT (OpenAI), under the author’s direction, assisted with critical review, consolidation, drafting, calculations, visual development and document preparation; the author retains responsibility.