{"id":"W3134712086","doi":"10.1016/j.acra.2020.12.026","title":"Review of Artificial Intelligence Training Tools and Courses for Radiologists","year":2021,"lang":"en","type":"review","venue":"Academic Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Alliance; Task (project management); Task force; Interpretation (philosophy); Training (meteorology); Radiology; Radiomics; Artificial intelligence; Applications of artificial intelligence; Medical physics; Medicine; Systems engineering; 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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002012162,0.0003862407,0.00434718,0.0003647442,0.00005486613,0.000006836372,0.0002854861,0.0008292114,0.000048244],"category_scores_gemma":[0.01024016,0.0002948872,0.0005419665,0.0004606779,0.0006324353,0.00003834219,0.00008042277,0.001848783,0.000002940729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005492895,"about_ca_system_score_gemma":0.0006184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003410707,"about_ca_topic_score_gemma":1.114585e-7,"domain_scores_codex":[0.9969186,0.0003823253,0.001500079,0.0006249148,0.000130828,0.0004432306],"domain_scores_gemma":[0.9959251,0.002716619,0.000729139,0.0003343498,0.0001028796,0.0001918843],"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":[0.000006934918,0.000009252643,0.000004434507,0.08416899,0.0002188418,0.00002349914,0.00005487187,4.132325e-7,0.000006373618,0.004149084,0.006217921,0.9051394],"study_design_scores_gemma":[0.00008072123,0.000153821,0.000001368115,0.1425168,0.001571459,0.003807985,0.00003810646,0.00008811101,0.000001828052,0.0003174681,0.8512161,0.0002061775],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000007653539,0.9925976,0.003993046,0.001449348,0.0004875031,0.001216046,0.00005745868,0.00003462429,0.0001566772],"genre_scores_gemma":[0.000003271583,0.99114,0.005132253,0.00205459,0.0008741179,0.0001665036,0.0005077845,0.00005404412,0.00006741092],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9049332,"threshold_uncertainty_score":0.9999503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1858780699395856,"score_gpt":0.4610928062336111,"score_spread":0.2752147362940255,"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."}}