{"id":"W4291020878","doi":"10.1016/j.ccell.2022.06.004","title":"Human and machine: Better at pathology together?","year":2022,"lang":"en","type":"letter","venue":"Cancer Cell","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Sinai Hospital","funders":"","keywords":"Computer science; Histopathology; Cancer; Big data; Pathology; Computational biology; Artificial intelligence; Data science; Bioinformatics; Medicine; Biology; Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001781826,0.0003004561,0.0005443202,0.00008140859,0.0002171119,0.00002018187,0.0001688139,0.0003696833,0.01304322],"category_scores_gemma":[0.0000156276,0.0002651585,0.0001292063,0.00005596429,0.0001809139,0.0000218865,0.0002676969,0.003064482,0.00002324479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003735223,"about_ca_system_score_gemma":0.00006458262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005597767,"about_ca_topic_score_gemma":0.00001344325,"domain_scores_codex":[0.99832,0.0001193428,0.0002571398,0.0005755915,0.0003120515,0.0004158311],"domain_scores_gemma":[0.9992378,0.00005622251,0.0001528519,0.0004119191,0.00002310228,0.0001181494],"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":[0.00001424866,0.00001524496,0.004691349,0.0004228884,0.00005209571,0.002661268,0.0002003861,0.000002648964,0.001717222,0.000001840707,0.9856573,0.004563522],"study_design_scores_gemma":[0.0009359077,0.0001431561,0.0005470221,0.0000553533,0.0002269764,0.0003133927,0.00001007947,0.0001224273,0.00009883656,0.00004140575,0.9972391,0.0002663077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06689719,0.01709414,0.00002920132,0.8876245,0.001343127,0.0004131036,0.00009503437,0.0001146742,0.02638905],"genre_scores_gemma":[0.002536157,0.0008900338,0.0002559524,0.9326143,0.004058854,0.0001166594,0.0005615022,0.0001415354,0.05882498],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06436104,"threshold_uncertainty_score":0.99998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494525181800219,"score_gpt":0.2844757969349722,"score_spread":0.2695305451169699,"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."}}