{"id":"W4307986809","doi":"10.18178/ijmlc.2022.12.6.1113","title":"A Machine Learning Ensemble Classifier for Cardiovascular Disease Taxonomy","year":2022,"lang":"en","type":"article","venue":"International Journal of Machine Learning and Computing","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Classifier (UML); Artificial intelligence; Machine learning; Ensemble learning; Taxonomy (biology)","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002953115,0.0001547411,0.0003429399,0.0002484363,0.001844088,0.00003610867,0.0003414203,0.00005029475,0.0002083212],"category_scores_gemma":[0.001357489,0.0001490127,0.0003709132,0.000111343,0.00003640776,0.000099432,0.0003979456,0.002192568,0.000007189388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002618673,"about_ca_system_score_gemma":0.0002715525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005716534,"about_ca_topic_score_gemma":0.00002037897,"domain_scores_codex":[0.9967597,0.001130509,0.0008451712,0.0002455208,0.0006758621,0.0003432278],"domain_scores_gemma":[0.9970101,0.001295347,0.0007751607,0.00009953996,0.0006215335,0.0001983877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007626115,0.00007500853,0.5507742,0.0001137528,0.0007346751,0.0001359153,0.002641885,0.2343244,0.00006441768,0.001779492,0.0003013081,0.2082923],"study_design_scores_gemma":[0.0006583671,0.000234733,0.001050015,0.0001583862,0.00007924584,0.00007710415,0.003159268,0.4789796,0.000006107932,0.0007618697,0.5146799,0.0001553329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7351506,0.02343727,0.2218145,0.008792775,0.007447883,0.001358746,0.00007177074,0.0001886807,0.001737812],"genre_scores_gemma":[0.9950516,0.0001609482,0.002188096,0.0004240256,0.001252372,0.00004028236,0.00003029677,0.00003514432,0.0008171871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5497242,"threshold_uncertainty_score":0.9994554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102513752845773,"score_gpt":0.4074249393713262,"score_spread":0.3049111865255532,"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."}}