{"id":"W4377564016","doi":"10.1148/radiol.230935","title":"Standalone AI in Breast Cancer Screening: Where We Are and What Is to Be Achieved","year":2023,"lang":"en","type":"letter","venue":"Radiology","topic":"AI in cancer detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Breast cancer; Mammography; MEDLINE; Breast imaging; Medical physics; Artificial intelligence; Gynecology; Cancer; Internal medicine; Computer science","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"],"consensus_categories":[],"category_scores_codex":[0.0002318482,0.0003355455,0.0005969689,0.0003943127,0.00008645385,0.0002515333,0.0008204563,0.0008135594,0.00004880043],"category_scores_gemma":[0.000009482497,0.0003368135,0.00006534693,0.0006262888,0.00009898232,0.0005748687,0.000417107,0.001423064,0.00002943867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003702015,"about_ca_system_score_gemma":0.0001293086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005755146,"about_ca_topic_score_gemma":0.001204983,"domain_scores_codex":[0.9975431,0.0002240447,0.0003066592,0.001053474,0.0002652596,0.0006074522],"domain_scores_gemma":[0.9988005,0.0001757932,0.0001710751,0.0006831872,0.0000782346,0.00009116869],"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":[0.00002487188,0.000003110387,0.0008877122,0.00009240769,0.00004862594,0.0002723821,0.0006813752,0.0000630535,0.00003731501,0.00001237803,0.9451056,0.05277119],"study_design_scores_gemma":[0.000444415,0.0001198302,0.009195761,0.0006133221,0.00001512753,0.0004090697,0.0000847183,0.001909183,0.00002235506,0.0003399703,0.9863542,0.0004920942],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0007512927,0.005166045,0.021516,0.9696548,0.002310244,0.0003011526,0.0001035042,0.0001868731,0.00001007489],"genre_scores_gemma":[0.0007153114,0.01560565,0.002180459,0.9765793,0.003134354,0.0002403454,0.00001922963,0.00008440399,0.001440966],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0522791,"threshold_uncertainty_score":0.9999084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661847674507099,"score_gpt":0.2786582009565708,"score_spread":0.2520397242114998,"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."}}