c1_protocol
plain-language theorem explainer
The declaration establishes that the C1 cognitive tensor combination satisfies the protocol-falsifiable predicate, confirming an associated dataset class, predicted observable, and failure mode exist in the registry. Researchers verifying empirical coverage for Recognition Science Option A predictions would cite this result for the C1 case. The proof is a direct one-line wrapper invoking the general protocolFalsifiable_all lemma.
Claim. The C1 cognitive tensor combination is protocol-falsifiable: there exist a dataset class $d$, predicted observable $o$, and failure mode $f$ such that datasetClass assigns $d$, predictedObservable assigns $o$, and failureMode assigns $f$ to this combination.
background
This module formalizes the falsifier registry as Lean propositions so every implemented C1-C9 combination carries a dataset class, predicted observable, and failure mode. ProtocolFalsifiable (c) is the predicate asserting such a triple exists with exact matches to the registry functions for combination c. The upstream theorem protocolFalsifiable_all proves the predicate for any combination by unfolding the definition and supplying the registry values via reflexivity.
proof idea
The proof is a one-line wrapper that applies protocolFalsifiable_all to the specific combination .c1CognitiveTensor.
why it matters
This theorem supplies the C1 coverage entry inside empiricalProtocolCert, which aggregates falsifier protocols across C1, C3, C5, and C8 to certify total coverage. It directly supports the module's guarantee that no implemented Option A theorem lacks an empirical falsifier protocol. The result closes one concrete instance in the chain of empirical testability for Recognition Science predictions.
Switch to Lean above to see the machine-checked source, dependencies, and usage graph.