{"id":"W4394611394","doi":"10.1016/j.cjca.2024.04.005","title":"Pattern Recognition and Inductive-Deductive Reasoning: 2 Cornerstones of Electrocardiogram Teaching","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Ottawa","funders":"","keywords":"Interpretation (philosophy); Consistency (knowledge bases); Medicine; Context (archaeology); Logical reasoning; Deductive reasoning; Reading (process); Artificial intelligence; Computer science; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02665788,0.0009528102,0.0009475175,0.003530469,0.001789103,0.008001904,0.003317759,0.003849256,0.004954112],"category_scores_gemma":[0.06006372,0.001035323,0.001127614,0.001880908,0.01072521,0.008082368,0.00527788,0.01024993,0.002976497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004903028,"about_ca_system_score_gemma":0.009333681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003650375,"about_ca_topic_score_gemma":0.004020106,"domain_scores_codex":[0.9800249,0.009736656,0.00138519,0.001527518,0.006522498,0.000803229],"domain_scores_gemma":[0.9304095,0.04660791,0.003610712,0.004852609,0.009804488,0.004714878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001747093,0.0006143719,0.008685701,0.001798396,0.00006817923,0.0008782798,0.01772106,0.0009932596,0.002645965,0.07544663,0.04326169,0.8477117],"study_design_scores_gemma":[0.0002363301,0.0003954374,0.0129118,0.005789639,0.00008200145,0.008510929,0.009831231,0.006240401,0.00562223,0.5606689,0.3894364,0.0002747036],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03504258,0.06740678,0.5137079,0.2746475,0.006606035,0.0008857374,0.0001968661,0.002265105,0.09924152],"genre_scores_gemma":[0.2568358,0.04425769,0.6383553,0.03974906,0.004657155,0.001167316,0.0002636687,0.0008352881,0.0138787],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02665788,"threshold_uncertainty_score":0.140982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403975473676409,"score_gpt":0.2694534560377324,"score_spread":0.2454137013009683,"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."}}