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theorem

branch_selection

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Why this theorem is linked from Cross Modality Image Translation In Medical Imaging Using Generative Frameworks unclear

Pith linked this Lean declaration because the review connected a specific passage in the paper to this theorem. The relation tag says how strong that connection is; it is not a generic placeholder.

The results show that GANs outperform latent generative models across all tasks, with SRGAN achieving statistically significant superiority.

Relation between the paper passage and the cited Recognition theorem.

module
IndisputableMonolith.Foundation.BranchSelection
domain
Foundation
line
173 · github
papers citing
1147 papers (below)

plain-language theorem explainer

The theorem asserts that if the RCL combiner with parameter c satisfies the coupling condition, then c must be nonzero. Researchers formalizing the Recognition Science composition law cite it to exclude the additive branch in favor of the bilinear representative. The proof is a direct one-line application of the forward direction of the RCL coupling equivalence.

Claim. If the combiner $P(u,v)=2u+2v+cuv$ is not separately additive, then $c≠0$.

background

The module formalizes branch selection under the strengthened composition consistency (L4*). A combiner is coupling when it is not separately additive, so that the interaction defect is nonzero for some pair of arguments. The RCL combiner is the polynomial $P(u,v)=2u+2v+cuv$ attached to the Recognition Composition Law family with free real parameter c. The upstream theorem RCLCombiner_isCoupling_iff states that this combiner is coupling if and only if c≠0.

proof idea

The proof is a one-line wrapper that applies the forward implication of RCLCombiner_isCoupling_iff to the supplied coupling hypothesis.

why it matters

This result forces the bilinear branch of the RCL family once the coupling requirement of the strengthened (L4*) is imposed. It is invoked by the contrapositive additive_branch_not_coupling and by the certificate branchSelectionCert. In the framework it completes the operator-level selection between the two branches of the RCL family, leaving only residual α-coordinate freedom for later calibration steps.

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