{"id":"W4400427682","doi":"10.1038/s44303-024-00026-2","title":"Author Correction: Artificial intelligence unravels interpretable malignancy grades of prostate cancer on histology images","year":2024,"lang":"en","type":"article","venue":"npj Imaging","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Prostate cancer; Malignancy; Artificial intelligence; Prostate; Medicine; Computer science; Cancer; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004727357,0.001821845,0.001864975,0.003770782,0.002355995,0.003391705,0.003451839,0.00560326,0.08356646],"category_scores_gemma":[0.1251487,0.001054718,0.001636298,0.002422769,0.002495057,0.001988446,0.002087093,0.00848238,0.03563205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114601,"about_ca_system_score_gemma":0.003659687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006265255,"about_ca_topic_score_gemma":0.007514919,"domain_scores_codex":[0.9937332,0.001164044,0.001358099,0.001135761,0.00212731,0.0004815777],"domain_scores_gemma":[0.9381248,0.0192371,0.002525376,0.00589251,0.03230021,0.001919889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008735168,0.000007298197,0.000199247,0.0003091887,0.00003796123,0.0006603707,0.00009509992,0.00009195047,0.0001909245,0.001267515,0.9867425,0.01031069],"study_design_scores_gemma":[0.0001185549,0.00004553952,0.00188023,0.0007728497,0.0001248419,0.004134299,0.0002331943,0.001140233,0.001564782,0.005561098,0.9843333,0.00009100069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0005929533,0.0008203794,0.003447963,0.04012239,0.9496202,0.00003742143,0.002054129,0.0009909411,0.00231352],"genre_scores_gemma":[0.09755976,0.009334104,0.03408271,0.1026247,0.4997469,0.0007012024,0.007872103,0.00803129,0.2400472],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08356646,"threshold_uncertainty_score":0.2795576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951773882064771,"score_gpt":0.3431405216929636,"score_spread":0.3236227828723159,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}