Softmax over SH2=256 features gives mask[i]=1/256=0.004 per feature,
collapsing the input signal 256×. Sigmoid gives mask[i]∈(0,1) independently
per feature. At W_vsn2=0 init: sigmoid(0)=0.5 → h_masked = 0.5*h_s2.
Shared memory reduced: SH2+R (no mask buffer needed, sigmoid is inline).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>