flymj

Uses the mushroom body's projection-to-Kenyon-to-output wiring as the fixed sparse structure of a network trained to predict Japanese mahjong discards, then runs the comparison most demos skip. Real wiring reaches 65.73 percent test accuracy, a degree-matched random rewiring 65.61 percent, and a parameter-matched dense network 65.29 percent. Both sparse arms beat the dense one clearly, while real against random is not significant. The author's reading is that the sparse expansion shape is what helps, not the fly's particular diagram. A playable app sits on top of the trained model.

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#mahjong#null-model#sparse-expansion#streamlit#negative-results#malecns