{"id":"W4402535105","doi":"10.1093/bjro/tzae029","title":"Accuracy of an artificial intelligence-enabled diagnostic assistance device in recognizing normal chest radiographs: a service evaluation","year":2023,"lang":"en","type":"article","venue":"BJR|Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hendrix Genetics (Canada)","funders":"","keywords":"Radiography; Service (business); Medicine; Computer science; Medical physics; Artificial intelligence; Radiology; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008642188,0.0006447297,0.0005169153,0.001990953,0.0002669198,0.001634765,0.001031437,0.0009912938,0.0007958729],"category_scores_gemma":[0.05555889,0.0002383528,0.0005455898,0.001425818,0.0008954249,0.001331151,0.001109651,0.0006105897,0.0005591034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101406,"about_ca_system_score_gemma":0.000698422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00426408,"about_ca_topic_score_gemma":0.003892923,"domain_scores_codex":[0.9935402,0.002547807,0.001058013,0.0006183172,0.001787176,0.0004484674],"domain_scores_gemma":[0.9642202,0.0199988,0.00585992,0.001529265,0.007289895,0.001101868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000507106,0.00005270539,0.9863244,0.00007556476,0.00008296341,0.0001297466,0.0001774867,0.0007713863,0.0003840805,0.0000472194,0.0001551812,0.01129213],"study_design_scores_gemma":[0.00005460818,0.002479176,0.948045,0.0000903284,0.0002607378,0.002443597,0.0008716444,0.0411114,0.003164724,0.0002521995,0.00119233,0.00003425874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951143,0.001158986,0.001715367,0.0002649013,0.00002011372,0.0000328554,0.0004177636,0.00005220341,0.001223404],"genre_scores_gemma":[0.9983562,0.0001404131,0.001075475,0.00002765455,0.00001715382,0.00000859483,0.0002875662,0.000004717332,0.00008221373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008642188,"threshold_uncertainty_score":0.04570478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4007621517611726,"score_gpt":0.4969738282180924,"score_spread":0.0962116764569198,"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."}}