Эксперимент: Branch-Length Polynomial Fingerprint (#1355)

{ "worked": true, "confidence": 8, "verdict": "Implemented the branch-length polynomial recursion and an M=8 log-magnitude fingerprint in a reusable module. The sanity check showed an exact ordinary-sum collision between two different rooted topologies, while polynomial evaluations differed by up to 49.32; classification accuracy was 0.50 for the baseline versus 1.00 with the fingerprint, and 0.9417 on an independent evaluation grid. This is a clear toy-level win, though not yet evidence for a full neural-encoder improvement.", "metrics": { "baseline": "Ordinary scalar sum: exact collision; classification accuracy 0.5000", "idea": "M=8 polynomial log-magnitude fingerprint: accuracy 1.0000 on fixed evaluation points, 0.9417 on held-out evaluation points; maximum raw polynomial separation 49.32" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py", "fingerprint.py", "results.txt" ], "limitations": "Only synthetic rooted trees and a scalar logistic-regression probe were tested; no TreeLSTM/GNN integration, real phylogenetic dataset, parameter-matched neural baseline, noise calibration, GPU benchmark, complex-valued features, or large-scale overflow study was performed." }