{"id":"W4387422232","doi":"10.3390/technologies11050138","title":"Heuristic Weight Initialization for Diagnosing Heart Diseases Using Feature Ranking","year":2023,"lang":"en","type":"article","venue":"Technologies","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"National Research Foundation of Korea; National Research Foundation","keywords":"Computer science; Initialization; Artificial intelligence; Heuristic; Machine learning; Classifier (UML); Feature (linguistics); Feature engineering; Deep learning","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":[0.001372986,0.001408357,0.001606328,0.001715671,0.0006843836,0.001096413,0.001822961,0.001865637,0.002984908],"category_scores_gemma":[0.004664177,0.0006121189,0.0008543729,0.001128977,0.0005476376,0.0008786011,0.0006905398,0.001469401,0.001525876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009022558,"about_ca_system_score_gemma":0.001760335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01068769,"about_ca_topic_score_gemma":0.01040179,"domain_scores_codex":[0.9994154,0.0001386677,0.00004733363,0.0001485924,0.0001353831,0.0001146882],"domain_scores_gemma":[0.9988843,0.0005596388,0.0001037052,0.00006948639,0.0003171224,0.00006584099],"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":[0.0004138238,0.0004201662,0.004149612,0.0001536325,0.0001095128,0.0002132983,0.00009449886,0.4854456,0.007865306,0.003774924,0.008543399,0.4888163],"study_design_scores_gemma":[0.0000239206,0.00005477627,0.0004487732,0.00001151929,0.00001427328,0.00003906278,0.00001043957,0.9966949,0.0009549809,0.001299579,0.0004386505,0.000009055172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05694758,0.001007899,0.936217,0.0005233769,0.0001724811,0.0002360937,0.0002046356,0.002125293,0.002565581],"genre_scores_gemma":[0.7153607,0.000386904,0.2781799,0.0005046735,0.000211373,0.0003432794,0.000846917,0.0002062408,0.003959919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01068769,"threshold_uncertainty_score":0.02125096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2371329315287754,"score_gpt":0.5158390178956147,"score_spread":0.2787060863668394,"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."}}