Weak supervision supports in-domain prediction of guide efficacy in CRISPR-Cas13d data but collapses under temporal shifts due to changing feature-label associations, while cross-cell-line transfer remains partial.
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Learning Stable Predictors from Weak Supervision under Distribution Shift
Weak supervision supports in-domain prediction of guide efficacy in CRISPR-Cas13d data but collapses under temporal shifts due to changing feature-label associations, while cross-cell-line transfer remains partial.