{"id":"W4237039320","doi":"10.1503/cmaj.081783","title":"Reading electrocardiograms","year":2009,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Neuroscience, Education and Cognitive Function","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reading (process); Computer science; Artificial intelligence; Computer graphics (images); Speech recognition; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006980691,0.0009908048,0.0004722655,0.0009414519,0.0004161455,0.001745774,0.0005538925,0.001563838,0.09918758],"category_scores_gemma":[0.01127708,0.0002038306,0.0003138072,0.0004855254,0.0005154501,0.002235392,0.0006565036,0.001871176,0.05403662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002309593,"about_ca_system_score_gemma":0.0002045648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004905889,"about_ca_topic_score_gemma":0.0006239286,"domain_scores_codex":[0.9994732,0.0001863977,0.00005905,0.00006052786,0.0001833627,0.00003745315],"domain_scores_gemma":[0.9974606,0.001267062,0.0001896884,0.0002838326,0.0005559478,0.0002427869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002457198,0.0001167377,0.003023406,0.0006705953,0.00004158679,0.003410675,0.001911195,0.0002441955,0.006540135,0.008001411,0.6066017,0.3691927],"study_design_scores_gemma":[0.00009903425,0.0002531433,0.01226779,0.001229297,0.00004255212,0.02280245,0.002193745,0.0004521193,0.002932675,0.0362348,0.92137,0.0001222926],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03565563,0.03075202,0.1555185,0.1205596,0.02236634,0.00063394,0.01140179,0.01651034,0.606602],"genre_scores_gemma":[0.3464517,0.0418115,0.1022792,0.06518377,0.02862223,0.0005342725,0.007246141,0.003871749,0.4039994],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09918758,"threshold_uncertainty_score":0.3318155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200579539970209,"score_gpt":0.2529404463328018,"score_spread":0.2409346509330997,"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."}}