{"id":"W2889407761","doi":"10.1007/s10459-018-9846-x","title":"How well is each learner learning? Validity investigation of a learning curve-based assessment approach for ECG interpretation","year":2018,"lang":"en","type":"article","venue":"Advances in Health Sciences Education","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"Royal College of Physicians and Surgeons of Canada","keywords":"Generalizability theory; Learning curve; Artificial intelligence; Inference; Machine learning; Competence (human resources); Computer science; Psychology; Social psychology; Developmental psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05252738,0.0004130286,0.0007514628,0.001942258,0.001115355,0.002704091,0.00162651,0.001296876,0.001289869],"category_scores_gemma":[0.2514997,0.0003196674,0.001265925,0.0008913645,0.001393337,0.003611106,0.003413621,0.001248316,0.000475662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002001299,"about_ca_system_score_gemma":0.003287969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002270134,"about_ca_topic_score_gemma":0.002905406,"domain_scores_codex":[0.966203,0.01466146,0.003935147,0.003012672,0.0113167,0.0008710616],"domain_scores_gemma":[0.708944,0.2007035,0.02117329,0.01527368,0.05090814,0.002997395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002034344,0.0008528681,0.8955384,0.000241922,0.0004949442,0.00006040607,0.00704255,0.001787075,0.001723835,0.00147677,0.0006449638,0.08810201],"study_design_scores_gemma":[0.0004380608,0.01081667,0.8833584,0.0006055731,0.0008633598,0.0007927541,0.01029487,0.06685467,0.01373247,0.00542939,0.006576429,0.0002373241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786586,0.0002324953,0.01485062,0.0004332579,0.00009843495,0.0006399382,0.000159748,0.00008171509,0.004845195],"genre_scores_gemma":[0.9910743,0.00005903813,0.007600166,0.0001051567,0.00001523597,0.0003013063,0.0001036489,0.00002665507,0.0007145656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05252738,"threshold_uncertainty_score":0.2777947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487636964115009,"score_gpt":0.4181191580885198,"score_spread":0.3693554616770189,"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."}}