c3_falsifier
The declaration asserts that the falsifier class for the oncology tensor combination equals the TCGA clinical response dataset. Cross-domain researchers anchoring Recognition Science theorems to empirical tests cite this to fix the C3 attachment. The proof reduces immediately to reflexivity on the registry definition.
claimThe empirical test class assigned to the oncology tensor combination equals the TCGA clinical response test class.
background
The Option A Falsifier Registry maintains a finite mapping from each of the nine C1-C9 cross-domain theorems to a dedicated empirical test class. This attachment keeps theoretical claims tied to observable data and blocks drift into unfalsifiable numerology, as stated in the module documentation. The upstream definition falsifierClass supplies the explicit case-by-case mapping, including the oncology tensor entry to the TCGA clinical response.
proof idea
The proof is a one-line reflexivity step on the definition of falsifierClass that confirms the C3 mapping without further reduction.
why it matters in Recognition Science
This entry populates the specific C3 mapping inside the falsifier registry, which the downstream falsifierRegistryCert aggregates through its counts of combinations, test classes, and observables. It directly supports the module's requirement that each cross-domain theorem carries an attached empirical falsifier.
scope and limits
- Does not prove the C3 theorem or any of its predictions.
- Does not perform empirical analysis or data validation.
- Applies only to the oncology tensor combination and its assigned test class.
formal statement (Lean)
175theorem c3_falsifier :
176 falsifierClass .c3OncologyTensor = .tcgaClinicalResponse := rfl
proof body
177