Biology Starter Pack

A runnable on-ramp, not the theory. Three short Python scripts reproduce the three portable signatures the kernel predicts wherever collapse operates under constraint — here dressed in biology framing. Run them, watch the shapes appear, then follow the hand-offs into the formal apparatus: the Methods paper that turns each signature into an audit, the Technical Note that proves its bound, and the deposited empirical test where one is live.

In biology: Ω is the space of organismal and population states; K physical laws plus environmental constraint and inherited structure; Cᴷₜ reproduction, variation, selection; Rₜ genomes, phenotypes, constructed niches; Sₜ metabolic waste and unstructured loss. Niche construction is the update map made vivid — organisms rewrite the constraints their descendants collapse under.

The signatures are domain-general, and that is the whole point. The engine that produces these shapes — `uct_signatures.py` — is byte-identical across the Physics, Biology, and Mind packs. Only the labels change. That the same code reproduces the same shapes in three domains is the claim the packs exist to make checkable in a minute. S₁ shows agreement saturating as independent pathways accumulate; S₂ shows commitment time peaking as the gradient flattens; S₃ shows sweep loops widening with built structure.

What these demos are. These demos are positive controls: they show the signatures can appear and how they would be measured. They are not evidence that any real biology system exhibits them — that work lives in the Tier 1.6 empirical demonstrations. The pack is built so that failure would be visible rather than hidden: each signature's falsifier is stated in the README, and the program-level version is in the Falsification Standards.

Keywords: starter pack; portable signatures; reproducibility; biology; runnable demo.