{"id":"W4379510727","doi":"10.1136/annrheumdis-2023-eular.4791","title":"POS0881 SPECIFIC AI-GENERATED PATTERN OF TENDER JOINTS AND TENDERNESS AT ENTHESIAL SITES ARE PREDICTIVE FOR OBJECTIVE DETECTION OF MUSCULOSKELETAL INFLAMMATION IN PSORIASIS PATIENTS","year":2023,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Fibromyalgia and Chronic Fatigue Syndrome Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Sanofi Genzyme; Genentech; Eli Lilly and Company; AstraZeneca; CSL Behring; Les Laboratories Pierre Fabre; Innovative Medicines Initiative; Biogen; European Federation of Pharmaceutical Industries and Associations; European Commission; Sanofi; CSL Limited; Pfizer","keywords":"Medicine; Psoriatic arthritis; Psoriasis; Enthesitis; Internal medicine; Dermatology","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":[0.000345913,0.000412967,0.0003194493,0.0006056276,0.0003360834,0.0007042137,0.000268616,0.0007843598,0.005566078],"category_scores_gemma":[0.001847949,0.0001726667,0.0003720433,0.0004672338,0.0002224719,0.0003728897,0.000266534,0.0007327166,0.001168442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001204408,"about_ca_system_score_gemma":0.0001180641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003803183,"about_ca_topic_score_gemma":0.000606495,"domain_scores_codex":[0.9996598,0.00008962343,0.00004115542,0.00007251382,0.00007089993,0.00006604593],"domain_scores_gemma":[0.998764,0.0003559153,0.0004367841,0.00005447732,0.0001337733,0.0002549341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001050407,0.0002093334,0.9835525,0.00003757883,0.00008058646,0.0007443501,0.00005088665,0.0000739352,0.007207165,0.0000704249,0.0004794546,0.006443426],"study_design_scores_gemma":[0.00002828621,0.0004482555,0.9945853,0.00001489854,0.00006271334,0.002945516,0.0001251285,0.0003147415,0.0006230339,0.0001297882,0.0007136419,0.000008738324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959775,0.0004548179,0.000149835,0.0001108912,0.000045039,0.00001364806,0.0003168567,0.000009852016,0.002921639],"genre_scores_gemma":[0.9986706,0.00009189423,0.0001482799,0.0001093085,0.00004536872,0.000008963424,0.0002434378,0.000003985222,0.0006781868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005566078,"threshold_uncertainty_score":0.01862043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03493034026551545,"score_gpt":0.30756908580447,"score_spread":0.2726387455389546,"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."}}