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Retire the bundled official classifier layer
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Select k under an outer fold, so the sweep stops grading its own choice
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Measure whether the classifier layer answers the same way twice
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Grade the classifier layer at family resolution, not per instrument
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Calibrate the layer eval per class instead of at one global threshold
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Add a cross-validated evaluation harness for the classifier layer