Agricultural evidence can be topically relevant yet conflict with the conditions of a query, or lack the information needed to support an action. We present MaizeEviReason, an auditable interface that keeps source conditions, distinguishes applicable, inapplicable and undetermined states, and separates applicability assessment from deterministic release checks. The core evaluation measures how much information is lost when conditions are projected onto fixed fields and what coverage is given up when supplied contracts are enforced. Matched learning experiments evaluate applicability prediction, and a public-pipeline diagnostic examines whether the interface is activated. On 49 constructed as... More >