{"id":"W4406808608","doi":"10.1017/cjn.2025.8","title":"EEG Training in the Context of Competency-Based Learning: When Is Enough, Actually Enough?","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Educational and Psychological Assessments","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Ottawa; Centre Hospitalier de l’Université de Montréal; University of Calgary; McMaster University; Dalhousie University; University of Toronto; University Health Network","funders":"","keywords":"Training (meteorology); Context (archaeology); Electroencephalography; Psychology; Computer science; Cognitive psychology; Artificial intelligence; Neuroscience; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.005929592,0.0003005577,0.0005540045,0.001021852,0.001495239,0.0003433522,0.003123773,0.0002217257,0.000986088],"category_scores_gemma":[0.001515622,0.0001761841,0.0002639647,0.001707325,0.005313726,0.0003735062,0.00003776717,0.001762671,0.000005352997],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001210966,"about_ca_system_score_gemma":0.005729862,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002066719,"about_ca_topic_score_gemma":0.02759838,"domain_scores_codex":[0.9943126,0.002182829,0.001119722,0.0005228065,0.0007175294,0.001144517],"domain_scores_gemma":[0.9958267,0.002138297,0.000849596,0.0001835055,0.0003796728,0.0006222875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002136352,0.0002149899,0.8995234,0.00001211888,0.00004468438,0.002029882,0.02867725,0.0008313599,0.00004501925,0.04310315,0.003957568,0.02134696],"study_design_scores_gemma":[0.001086409,0.05827327,0.7043144,0.0001274718,0.0000662349,0.004243159,0.02508932,0.0003137309,0.00004050052,0.169801,0.03616614,0.0004784034],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399402,0.0009058307,0.00003428071,0.03403711,0.001303241,0.0001877015,0.00001126442,0.000008663418,0.02357172],"genre_scores_gemma":[0.9770716,0.00004970991,0.001253732,0.02138705,0.0001110373,0.000007694512,5.147201e-7,0.000006074549,0.000112598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.195209,"threshold_uncertainty_score":0.9999272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0667975110713896,"score_gpt":0.3492746756947159,"score_spread":0.2824771646233263,"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."}}