{"id":"W2977601947","doi":"10.1148/radiol.2019191586","title":"Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement","year":2019,"lang":"en","type":"article","venue":"Radiology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":367,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; University of Alberta","funders":"","keywords":"Medicine; Transparency (behavior); Cornerstone; Informatics; Dignity; Harm; Radiology; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001019534,0.00008663102,0.0003499935,0.00005652602,0.00003102036,0.000001465914,0.00009412716,0.00007162905,0.0000206807],"category_scores_gemma":[0.0004216399,0.00006284892,0.00005640636,0.000252705,0.0006362706,0.00002071212,0.00005111694,0.0004455553,0.000008944045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006320416,"about_ca_system_score_gemma":0.0001875515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001132425,"about_ca_topic_score_gemma":0.0007881285,"domain_scores_codex":[0.998338,0.0005014443,0.0006646302,0.0002021546,0.0000970176,0.0001967162],"domain_scores_gemma":[0.9989129,0.0003993995,0.0002675597,0.0002644116,0.0001052596,0.00005044393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001342821,0.0001218415,0.8578648,0.0001842547,0.00003071422,0.000002917266,0.01183022,0.0002581353,0.006851758,0.001161742,0.000128366,0.121431],"study_design_scores_gemma":[0.00005566133,0.001267782,0.9759134,0.0001170567,0.00002815602,0.00005195005,0.008274977,0.002545899,0.01050869,0.0006668121,0.0004529323,0.0001166623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996185,0.0002990804,0.0003500907,0.002255555,0.0003451398,0.0003845062,0.00000622858,0.000006728649,0.0001676505],"genre_scores_gemma":[0.997547,0.001138334,0.0006628791,0.0005310656,0.00006891247,0.000004852331,0.00001012651,0.000009036668,0.00002776703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1213143,"threshold_uncertainty_score":0.2562905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1474693501437812,"score_gpt":0.3987601671631053,"score_spread":0.2512908170193242,"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."}}