{"id":"W2040575592","doi":"10.1016/j.jelectrocard.2005.08.013","title":"Development of an automated Selvester Scoring System for estimating the size of myocardial infarction from the electrocardiogram","year":2005,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Myocardial infarction; Set (abstract data type); Computer science; Scoring system; Cardiology; Internal medicine; Medicine; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001596874,0.0001734522,0.0008594223,0.0000965371,0.000134617,0.00001723023,0.0001898743,0.0001149124,0.000001107726],"category_scores_gemma":[0.0009815973,0.0001027101,0.0005187165,0.0002114674,0.0000948494,0.00009808216,0.00002979486,0.0003564665,9.823783e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001802237,"about_ca_system_score_gemma":0.0005827028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001786079,"about_ca_topic_score_gemma":0.00000489276,"domain_scores_codex":[0.9979986,0.0002383337,0.0009486965,0.0001537563,0.0003301497,0.000330439],"domain_scores_gemma":[0.9969088,0.001463271,0.0007244604,0.0002890195,0.0005358802,0.0000786054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00546306,0.0004395606,0.1650291,0.0005153695,0.01646554,0.00006085086,0.007122067,0.03643499,0.6308603,0.0004867117,0.004160496,0.1329619],"study_design_scores_gemma":[0.009209002,0.003544952,0.7795257,0.001075783,0.005275422,0.007889734,0.002077435,0.03174032,0.1504053,0.000203463,0.008516042,0.0005368265],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653921,0.001159843,0.0316782,0.0005445363,0.0005997338,0.000385345,0.000005512426,0.00005668804,0.0001780091],"genre_scores_gemma":[0.9304963,0.00001960139,0.06729196,0.0001988993,0.001942847,0.00001470787,0.00000908751,0.00002407599,0.000002543808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6144966,"threshold_uncertainty_score":0.4188397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122749774948614,"score_gpt":0.2912180339254352,"score_spread":0.2789430564305738,"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."}}