IndisputableMonolith.Foundation.OptionAEmpiricalReadiness
This module defines empirical readiness for Option A combinations in Recognition Science. A combination is empirically ready precisely when all operational records from its pipeline exist. It supplies the EmpiricallyReady predicate and aggregate lemmas for the C1-C9 set. These feed directly into the Option A Empirical Program module to certify the assembled first-pass program. The module is a collection of predicate definitions and simple aggregate statements.
claimA combination $c$ satisfies $\text{EmpiricallyReady}(c)$ if and only if every operational record in its pipeline $\mathcal{P}(c)$ exists. Related predicates include $\text{FirstPassReady}$ and $\text{AllImplementedReady}$, with aggregate claims such as $\text{empiricallyReady_all}$ asserting the property uniformly over implemented combinations.
background
The upstream Option A Empirical Pipeline module supplies the unified record structure that ties protocol, priority, analysis action, and deliverable for every implemented Option A combination (C1-C9). This module operates in the foundation layer of Recognition Science, where empirical readiness serves as the metadata-level gate before any execution schedule or deliverable is invoked. The DOC_COMMENT states the core rule: a combination is empirically ready when all operational records exist.
proof idea
This is a definition module, no proofs. It declares the EmpiricallyReady predicate together with sibling definitions (FirstPassReady, AllImplementedReady) and aggregate lemmas (empiricallyReady_all, scheduled_empiricallyReady) that follow directly from the pipeline record structure.
why it matters in Recognition Science
This module supplies the readiness predicates and aggregate statements consumed by the Option A Empirical Program module, which assembles them into a single certificate asserting that the first-pass empirical program is complete and collision-free at the metadata layer. It closes the gap between the pipeline definitions and the program-level claim in the Recognition Science empirical verification chain.
scope and limits
- Does not verify physical existence or content of any empirical record.
- Does not address combinations outside the implemented C1-C9 set.
- Does not prove collision-freeness or completeness at the full program execution level.
- Does not incorporate scheduling, priority, or action details beyond record existence.