{"id":"W3005891124","doi":"10.1016/j.acra.2020.01.012","title":"Noninterpretive Uses of Artificial Intelligence in Radiology","year":2020,"lang":"en","type":"review","venue":"Academic Radiology","topic":"AI in cancer detection","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Computer science; Artificial intelligence; Task (project management); Applications of artificial intelligence; Action (physics); Expert system; Medical physics; Radiology; Medicine; Engineering","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"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0006338153,0.0004320854,0.002430048,0.001200501,0.00002884258,0.000008438881,0.002723336,0.001425196,0.00002201538],"category_scores_gemma":[0.0005343005,0.0003936914,0.0003177412,0.00219339,0.0004390448,0.0001789596,0.0005418758,0.002328607,0.0001174062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003484362,"about_ca_system_score_gemma":0.0005248617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004029867,"about_ca_topic_score_gemma":0.000007120418,"domain_scores_codex":[0.9956617,0.001109615,0.001557147,0.001036762,0.000146049,0.0004887122],"domain_scores_gemma":[0.996914,0.001453794,0.0009017559,0.0005940569,0.00004181903,0.00009463295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009022677,0.000006487464,0.000003776114,0.0006305445,0.0000571659,0.00003412214,0.0004749954,0.00003074219,0.000008173428,0.02460676,0.0003298331,0.9738084],"study_design_scores_gemma":[0.00004063645,0.0003787179,0.0000032894,0.002348241,0.00008802563,0.001429727,0.00002505855,0.003397971,0.00008677928,0.01102113,0.980714,0.0004664189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004971212,0.8498719,0.1475957,0.000245529,0.001488035,0.0004735717,0.00001050233,0.00007925971,0.0002305828],"genre_scores_gemma":[0.0001971187,0.9952747,0.00379597,0.0001266866,0.0004272274,0.0001315451,0.000006926928,0.00002907923,0.00001081016],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9803842,"threshold_uncertainty_score":0.9999731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07048308614967656,"score_gpt":0.3710884946957462,"score_spread":0.3006054085460696,"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."}}