{"id":"W3115123278","doi":"10.1002/mus.27163","title":"Neuromuscular ultrasound competency assessment: Consensus‐based survey","year":2020,"lang":"en","type":"article","venue":"Muscle & Nerve","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Delphi method; Medicine; Medical physics; Delphi; Specialty; Quality assessment; Ultrasound; Nominal group technique; Medical education; Competency assessment; Physical therapy; Physical medicine and rehabilitation; Knowledge management; Family medicine; Computer science; Pathology; External quality assessment; Artificial intelligence; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004966432,0.000235538,0.0004667278,0.00004170095,0.0001379687,0.00005008772,0.000242289,0.0001336413,0.001177321],"category_scores_gemma":[0.00186572,0.0002194762,0.0002434885,0.0005686286,0.0001834678,0.00003970083,0.00004257844,0.0005423375,0.000358373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005061726,"about_ca_system_score_gemma":0.0003387386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000206695,"about_ca_topic_score_gemma":0.00003996155,"domain_scores_codex":[0.9977205,0.0002852812,0.0005865297,0.0006035633,0.0004484131,0.0003557587],"domain_scores_gemma":[0.9956298,0.002779434,0.000151838,0.0006760437,0.0002503415,0.0005125195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002175929,0.001631297,0.8000708,0.0002805976,0.0002312331,0.0001549557,0.0002280498,0.0001827228,0.1663614,0.003477135,0.02517688,0.001987356],"study_design_scores_gemma":[0.001713267,0.0004131887,0.9663138,0.00002409419,0.0001167911,0.00001404152,0.00003789224,0.001754713,0.0005202788,0.0001926859,0.02866719,0.0002320367],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709013,0.00006495292,0.002818083,0.01733401,0.0001343013,0.0007479455,0.0001894376,0.0003279531,0.007482023],"genre_scores_gemma":[0.9781588,0.00001277623,0.008845854,0.01201265,0.0002279504,0.00004976561,0.0005325567,0.00005563831,0.0001039806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.166243,"threshold_uncertainty_score":0.9997357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07808616431093032,"score_gpt":0.3464689639517643,"score_spread":0.268382799640834,"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."}}