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Globally, over 15 million people are living with spinal cord injury. We built a cross-species contrast to surface CNS-regeneration targets the field has overlooked: spinal-cord and appendage regeneration in three regeneration-competent species against mammalian injury, compared at the human-ortholog level. From a 1,034-dataset catalog we derived a 587-gene "competent-not-in-mammal" signature, scored 123 candidate targets, and annotated each for druggability. A from-scratch physics and control-theory engine adds what a differential-expression list cannot: causal direction, and evidence that no single perturbation reaches a four-way cocktail ceiling — so the robust targets are convergent downstream effectors (19 of 73 druggable now). The shipped ranking is what survived our own engine attacking it twice. Its first pick (MATK #1) was a near-zero-baseline artifact; a Claude self-audit caught it and re-ranked to COL9A1, which then held across five orthogonal axes — all directional and nominal, hypothesis not proof. It matters because it is reproducible, uses public data and APIs only, and every number opens to an artifact others can build on: a prioritized, falsifiable hypothesis set.

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