New Calibration Framework Improves Confidence in AI Virtual Cell Models
Across 14 genetic perturbation datasets and 18 evaluation metrics, commonly used measures such as mean squared error and control-referenced Pearson correlation were often poorly calibrated, particularly in datasets with weaker perturbations. The post New Calibration Framework Improves Confidence in AI Virtual Cell Models appeared first on GEN - Genetic Engineering and Biotechnology News .
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