{"id":"W2751926322","doi":"10.1002/aet2.10064","title":"Sonographic Accuracy as a Novel Tool for Point‐of‐care Ultrasound Competency Assessment","year":2017,"lang":"en","type":"article","venue":"AEM Education and Training","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University; Cancer Care Ontario","keywords":"Medicine; Point of care ultrasound; Point of care; Curriculum; Competency assessment; Ultrasound; Physical therapy; Medical physics; Psychology; Radiology; Medical education; Nursing","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002409565,0.0001102627,0.0002374942,0.00006621648,0.0003918334,0.00008231909,0.0001387474,0.00007202647,0.00008592026],"category_scores_gemma":[0.00156279,0.0001024708,0.0001094132,0.00006138447,0.0001762676,0.0001635892,0.00001697771,0.0001399917,0.000004489243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002327104,"about_ca_system_score_gemma":0.0007160686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003717923,"about_ca_topic_score_gemma":0.00001072043,"domain_scores_codex":[0.9991205,0.00000935719,0.0003349742,0.0002551621,0.0001253297,0.0001546789],"domain_scores_gemma":[0.9977425,0.001104645,0.0002889255,0.0004757906,0.0002741429,0.0001140181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001235632,0.002060037,0.3132651,0.0006917996,0.0002826191,3.373951e-7,0.01405833,0.000001072891,0.02229765,0.3292934,0.0009498043,0.3169764],"study_design_scores_gemma":[0.001732167,0.0003700691,0.9613292,0.00022209,0.0001894339,0.00006049094,0.009948087,0.00003276074,0.0003071868,0.009932508,0.01570264,0.0001734009],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711178,0.0001673584,0.00334785,0.00530589,0.0002901128,0.0009190186,0.00003257814,0.00003964205,0.01877975],"genre_scores_gemma":[0.9330747,0.00008719842,0.06527202,0.0008042687,0.0001872988,0.0002391389,0.0001287544,0.00001607511,0.0001905558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6480641,"threshold_uncertainty_score":0.4178638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06990355109067514,"score_gpt":0.4350441357814792,"score_spread":0.3651405846908041,"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."}}