{"id":"W4285101299","doi":"10.1109/aiiot54504.2022.9817370","title":"An Approach for Automatic Discovery of Rules Based on ECG Data Using Learning Classifier Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE World AI IoT Congress (AIIoT)","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Machine learning; Classifier (UML); Artificial intelligence; Component (thermodynamics); Personalized medicine; Decision support system; Association rule learning; Data mining; Bioinformatics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003307894,0.0008482691,0.001067012,0.00290003,0.0007951576,0.002536472,0.002211505,0.001616891,0.001974518],"category_scores_gemma":[0.01465712,0.0005496591,0.001059096,0.001855621,0.0007050716,0.001837178,0.0009898674,0.001851372,0.00103816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009784508,"about_ca_system_score_gemma":0.001861535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006789932,"about_ca_topic_score_gemma":0.005834321,"domain_scores_codex":[0.9965064,0.0006590805,0.0004132492,0.0008113128,0.001454978,0.0001549637],"domain_scores_gemma":[0.992755,0.003613002,0.0004370951,0.0009423352,0.00213134,0.0001213746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001771354,0.0003406767,0.007080456,0.0002731095,0.0002063191,0.0006048954,0.000437669,0.08213249,0.01823972,0.01963983,0.004930289,0.8659375],"study_design_scores_gemma":[0.00003405931,0.0001127261,0.001720272,0.00008265295,0.00008988577,0.0003116079,0.0000983387,0.9487567,0.01938633,0.01826111,0.01109658,0.00004963935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007721289,0.0001850673,0.9877113,0.0002876629,0.0000574127,0.0002539502,0.0001929902,0.002328523,0.001261838],"genre_scores_gemma":[0.1014596,0.00020225,0.89588,0.0001824124,0.00004663498,0.000254611,0.0005022769,0.0001028065,0.001369515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006789932,"threshold_uncertainty_score":0.01749402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05134884789720748,"score_gpt":0.3044739133264933,"score_spread":0.2531250654292858,"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."}}