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A groundbreaking watermarking method that not only traces LLM-generated content but also detects tampering with unprecedented accuracy.
An in-cell method that sensitively detects rare off-target edits, benchmarks performance across editors, and improves risk assessment in therapeutic cells is presented, establishing UNCOVERseq as a robust framework for informed off-target risk assessment in translational gene-editing systems.