{"id":"W2784109320","doi":"10.1109/glocom.2017.8254451","title":"Performance Assessment of Decision Tree-Based Predictive Classifiers for Risk Pregnancy Care","year":2017,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Decision tree; Computer science; Classifier (UML); Decision tree learning; Statistic; Cohen's kappa; Data mining; Decision support system; Machine learning; Artificial intelligence; Health care; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007669433,0.001390297,0.001530495,0.002975686,0.0007894472,0.001386937,0.001046883,0.001284365,0.001361397],"category_scores_gemma":[0.01535943,0.0002515501,0.001251812,0.00154924,0.0002440601,0.001263746,0.0007274473,0.001195271,0.0007778747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225407,"about_ca_system_score_gemma":0.001658357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01154915,"about_ca_topic_score_gemma":0.004542011,"domain_scores_codex":[0.9971038,0.001173862,0.0003354436,0.0003659187,0.0007115204,0.0003095283],"domain_scores_gemma":[0.9887033,0.008004357,0.0004240461,0.0003842758,0.002151616,0.0003324641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00447579,0.001268509,0.1037086,0.0006362545,0.0008958383,0.0003815865,0.0004073462,0.3785984,0.003268694,0.002266361,0.009282361,0.4948103],"study_design_scores_gemma":[0.00003383104,0.000469065,0.007881812,0.00008619736,0.0001805667,0.0001073195,0.0001390349,0.9870719,0.002133631,0.0009848827,0.0008858975,0.00002591821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8402693,0.008899133,0.1352311,0.001721357,0.0008886381,0.0003713804,0.002779412,0.001440379,0.00839933],"genre_scores_gemma":[0.9658991,0.001101828,0.02914435,0.0001188973,0.0001188422,0.0001366614,0.00228305,0.00003510974,0.001162016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01154915,"threshold_uncertainty_score":0.04056031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1771122418983703,"score_gpt":0.530289256404475,"score_spread":0.3531770145061047,"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."}}