{"id":"W4404107887","doi":"10.1148/ryai.240334","title":"RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes","year":2024,"lang":"en","type":"article","venue":"Radiology Artificial Intelligence","topic":"Abdominal Trauma and Injuries","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Vancouver General Hospital; North York General Hospital; Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"St. Michael's Hospital Foundation","keywords":"Medicine; Receiver operating characteristic; Extravasation; Radiology; Artificial intelligence; Nuclear medicine; Internal medicine; Computer science; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004948445,0.0002416249,0.0006816153,0.0001338736,0.0001080571,0.00002991253,0.0001199145,0.0001778107,0.001467415],"category_scores_gemma":[0.000264071,0.0001833064,0.0001644063,0.0002240886,0.0005600876,0.0001277188,0.00003973588,0.0004834112,0.0009360209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003795324,"about_ca_system_score_gemma":0.00007242699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001664121,"about_ca_topic_score_gemma":0.00001843876,"domain_scores_codex":[0.9984032,0.00008915795,0.0005395829,0.0004823829,0.0001340996,0.0003515767],"domain_scores_gemma":[0.9991617,0.000299131,0.00004283133,0.0002696703,0.00006809558,0.0001585751],"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":[0.0003141909,0.0001757898,0.0005367372,0.003022153,0.0003676841,0.0006368366,0.0007862758,0.0000018972,0.001144599,0.1148949,0.02155961,0.8565593],"study_design_scores_gemma":[0.0006350683,0.01110931,0.02964257,0.0133257,0.007841564,0.01486279,0.003768099,0.01053272,0.04773404,0.2213826,0.635335,0.003830517],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1224715,0.6244324,0.01819404,0.2055576,0.002543284,0.002176418,0.00006455695,0.0006533198,0.02390696],"genre_scores_gemma":[0.9613342,0.02904547,0.000763552,0.005120533,0.0004744047,0.00006770363,0.0000118706,0.00003388409,0.003148424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8527288,"threshold_uncertainty_score":0.9998419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06355374889793619,"score_gpt":0.386173024129926,"score_spread":0.3226192752319899,"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."}}