ML Experiment Methodology

A 0.0030 ensemble win against a 0.0098 noise band: these benchmarks are measuring their own seeds

Six self-reported write-ups on stacking, voting, blending and search kept landing inside their own seed spread. The clearest result was procedural: in-fold stacking weighted the worse model 32 to 1.