Mutation by Natural Dominance (TMD): analysis‑only toolkit v2.3 — real‑system readiness, uncertainty, and multi‑route coherence (with WS pilot case study)

Short description Mutation by Natural Dominance (TMD) is a testable framework for predicting which adaptive genetic route appears first when multiple solutions exist. It models “first winners” as a hazard race: the chance a route wins first is proportional to its successful‑arrival hazard λ. In genetics, λᵢ ∝ μᵢ·Aᵢ·Fᵢ (mutation supply × accessibility/context × fixation/persistence). In origins chemistry, an analogous CDI uses λₖ ∝ kₖ·aₖ·fₖ. This v2.3 release extends the v2.2 analysis‑only toolkit with real‑system readiness templates + a one‑run pipeline, robust uncertainty for overdispersed (non‑i.i.d.) replicates, a multi‑route graph‑coherence test (K≥3), and a pilot literature‑based case study on *Pseudomonas fluorescens* “Wrinkly Spreader” routes. Long description Mutation by Natural Dominance (TMD) — v2.3 **Status:** testable framework (pre‑theory). When preregistered gates G1–G3 (and ideally G4) pass across real systems and independent labs, it becomes reasonable to use: “The Theory of Mutation by Natural Dominance (TMD)”. Until then, this remains a framework / hypothesis family rather than a finished Theory. ## Core ideaEvolution often follows the “easiest” route. TMD quantifies “ease” via a hazard‑level model of first successful arrivals: - **Genetics:** λᵢ ∝ μᵢ Aᵢ Fᵢ - **Origins chemistry:** λₖ ∝ kₖ aₖ fₖ where λ is a successful‑arrival hazard (a first‑arrival rate), μ is mutation/variation supply, A is genome accessibility / context, and F is a fixation/persistence factor from population genetics. For chemistry, k is an effective reaction/network rate, a is accessibility (concentrations, surfaces, cycling, compartments), and f is persistence/continuation. First fixation is a Poisson race: P_first,i = λᵢ / Σⱼ λⱼ, giving a softmax/logistic law over competing routes. ## What’s new in v2.3This release is about making TMD **test‑ready on real systems**, with robust uncertainty and multi‑route coherence checks. ### 1) Real‑system readiness (templates + one‑run pipeline)A practical pack with templates for route definitions and winner counts, plus a script that produces: - winner fractions \(\hat P\) - path entropy \(H\), \(N_\text{eff}\), predictability \(\Pi\) - pairwise dominance \(\delta_{ij}\) (log2) and uncertainty - predicted \(P\) from μ·A·F when provided, and comparison reports ### 2) Overdispersion / non‑i.i.d. replicatesReal replicate experiments can show extra variance beyond binomial/multinomial sampling. v2.3 adds robust inference options (beta‑binomial / Dirichlet‑multinomial style logic and an effective replicate number \(n_\text{eff}\)) so δ and entropy estimates are not over‑confident. ### 3) Information ridge + prereg blocks for G3 designGiven a target dominance δ, v2.3 provides notes/tables for choosing replicate number n based on:- required power, and/or- desired CI width on \(\delta\) and on predictability metrics (entropy / \(N_\text{eff}\)). ### 4) Multi‑route graph coherence (K≥3)For K≥3 routes, pairwise dominance \(\delta_{ij}\) should approximately behave like a single potential field (\(\delta_{ij} \approx \phi_i-\phi_j\)) in “one‑axis dominance” systems. v2.3 includes a cycle‑closure / graph‑curl test that can falsify that assumption or detect hidden structure. ### 5) Pilot literature‑based case study (WS routes)A worked example on *Pseudomonas fluorescens* “Wrinkly Spreader” (WS) routes (Wsp/Aws/Mws). Using:- derived pathway counts (n=26) from a published genotype table, and- published pathway mutation rates to WS,the case study demonstrates how TMD can infer relative fixation/persistence factors when μ‑supply and observed route outcomes differ. ## What this release is NOTThis record is **analysis‑only**:- no lab protocols, - no new biological data, - no claim of experimental validation. It provides a transparent mathematical framework, templates, and synthetic/literature demonstrations designed to be tested and potentially falsified by independent labs.