{"id":"W3165603187","doi":"10.1136/annrheumdis-2021-eular.3343","title":"POS0036 AN ARTIFICIAL INTELLIGENCE MODEL IN RHEUMATOLOGY: INTERPRETATION OF THE SACROILIAC JOINT GRAPHY IN ANKYLOSING SPONDYLITIS","year":2021,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Alberta; Université de Sherbrooke; University of Calgary","keywords":"Ankylosing spondylitis; Medicine; Radiography; Sacroiliac joint; Radiology; Artificial intelligence; Rheumatology; Physical therapy; Medical physics; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002382113,0.0001102466,0.0003319658,0.0001314405,0.00002680134,0.00001790162,0.0002540259,0.0000365503,0.00004892167],"category_scores_gemma":[0.0006888069,0.0000771162,0.0002031624,0.0006179084,0.0001467397,0.0001490946,0.00006270786,0.0001232362,0.000001057058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001130038,"about_ca_system_score_gemma":0.00005562822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001141558,"about_ca_topic_score_gemma":0.00009566205,"domain_scores_codex":[0.9986631,0.000179623,0.0006264534,0.0001359299,0.000219661,0.0001751772],"domain_scores_gemma":[0.9992573,0.0001268641,0.0001081999,0.000385631,0.00006698557,0.0000549971],"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":[0.00003615356,0.0006467082,0.02282603,0.001857294,0.0002046619,0.000007234106,0.006136652,0.8197499,0.001647213,0.006125464,0.000278242,0.1404845],"study_design_scores_gemma":[0.00004432085,0.000005355168,0.009306869,0.001906377,0.00003183722,0.000002358182,0.0007599451,0.928564,0.008874424,0.05041568,9.764626e-7,0.00008782508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991952,0.001376397,0.005667116,0.0006766843,0.000108185,0.00007380307,0.00006260027,0.00001926568,0.00006396766],"genre_scores_gemma":[0.9993697,0.0003337669,0.0001997365,0.00006033463,0.000002281793,0.000007179013,0.00001027809,0.0000105938,0.000006150467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1403966,"threshold_uncertainty_score":0.3144707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04183304547471996,"score_gpt":0.2886013446776275,"score_spread":0.2467682992029076,"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."}}