Where one study disagrees with what other studies report for the same models, and what we are doing to resolve each case.
These are automatic leads, not findings of error. Each release, a check compares how every study ranks the models it shares with other studies. It flags a study that reverses the order the others agree on, or whose gap to a shared reference model lies well outside theirs. Different tasks, populations or metrics often explain a flag.
A flag never hides a result. Flagged results stay in every table, page and download, marked Contested. A result is withheld only when a reviewer marks it disputed.
Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants ranks ChromBPNet above Caduceus in 4 of 4 comparisons; other studies rank Caduceus above ChromBPNet in 6 of 6.
GUANinE v1.1 reveals complementarity… ranks Caduceus above ChromBPNet in all 6 of its comparisons. Comparative Analysis of Deep Learning… ranks ChromBPNet above Caduceus in all 4 of its comparisons.