{"id":"W4294816830","doi":"10.1080/10903127.2022.2120934","title":"Deriving National Continued Competency Priorities for Emergency Medical Services Clinicians","year":2022,"lang":"en","type":"article","venue":"Prehospital Emergency Care","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Thematic analysis; Delphi method; Medicine; Medical education; Certification; Content analysis; Likert scale; Descriptive statistics; Checklist; Delphi; Emergency medical services; Family medicine; Nursing; Medical emergency; Psychology; Qualitative research; Management","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004541757,0.0002601632,0.0003819605,0.0001931705,0.0007764935,0.00001061684,0.0003529794,0.0001348061,0.01379714],"category_scores_gemma":[0.000401264,0.0002950321,0.000325015,0.0004279169,0.00004307197,0.0001559114,0.0001493582,0.0004173267,0.00002613188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004145967,"about_ca_system_score_gemma":0.001586683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002507278,"about_ca_topic_score_gemma":0.0001532031,"domain_scores_codex":[0.9962177,0.0001205935,0.001086878,0.0005572321,0.00154878,0.00046883],"domain_scores_gemma":[0.9970677,0.0002044931,0.0002915577,0.000344791,0.001775408,0.0003160218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009914367,0.0001869057,0.9734244,0.001489399,0.00009433314,0.000005012342,0.01499685,0.000215532,0.0000302077,0.001934144,0.005705465,0.00181866],"study_design_scores_gemma":[0.002647176,0.001342131,0.8860381,0.0002179796,0.0001933514,0.00002993901,0.06998695,0.005364261,0.00006992924,0.003762568,0.02952382,0.0008238506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705768,0.007694582,0.0001580747,0.005462513,0.009578466,0.001924326,0.0005371093,0.0002688188,0.003799328],"genre_scores_gemma":[0.993959,0.0001893795,0.0007889595,0.0006646709,0.001233722,0.001230902,0.001045601,0.00007039506,0.000817386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08738631,"threshold_uncertainty_score":0.9999502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02454432858198004,"score_gpt":0.3762874610499933,"score_spread":0.3517431324680133,"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."}}