{"id":"W3035576270","doi":"10.18280/ria.340212","title":"Musculoskeletal Abnormality Detection in Humerus Radiographs Using Deep Learning","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Abnormality; Radiography; Humerus; Medicine; Artificial intelligence; Orthodontics; Computer science; Radiology; Anatomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000242803,0.0001368312,0.0002081102,0.0001369884,0.00008366929,0.00003580818,0.0001352126,0.00006612101,0.0002037606],"category_scores_gemma":[0.0001325447,0.0001489113,0.0001451215,0.001003663,0.00005338181,0.000126435,0.00002428001,0.0004169699,0.0001189006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004182418,"about_ca_system_score_gemma":0.000005058577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008885155,"about_ca_topic_score_gemma":0.00001772843,"domain_scores_codex":[0.9989136,0.00006054236,0.0003648788,0.0002375666,0.0001304981,0.0002929026],"domain_scores_gemma":[0.9996019,0.00005239015,0.00003493651,0.0001364227,0.00002392153,0.0001504281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002036228,0.00001451243,0.002702052,0.0001074721,0.00001920574,0.00002299484,0.001070564,0.8473455,0.0152061,0.00001444722,0.00000521838,0.1334898],"study_design_scores_gemma":[0.00002598296,0.00001759682,0.0001374494,0.00003268562,0.00002146241,0.000007578832,0.0008455109,0.9750693,0.02284339,0.00003934607,0.0007954843,0.0001642063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.543927,0.0005361763,0.4544342,0.00007237894,0.0001123986,0.00005708492,4.338797e-7,0.0001907638,0.0006696053],"genre_scores_gemma":[0.9990162,0.0001746111,0.0006049971,0.0000399409,0.0001136712,0.000005157916,0.000003412939,0.00002121705,0.00002084584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4550892,"threshold_uncertainty_score":0.6072426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02535258753172763,"score_gpt":0.2589608961912152,"score_spread":0.2336083086594876,"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."}}