{"id":"W4386159467","doi":"10.23919/fusion52260.2023.10224085","title":"DEMDE: Decision Making Design based on Bayesian Network for Personalized Monitoring System","year":2023,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Robustness (evolution); Bayesian network; Decision support system; Domain (mathematical analysis); Reliability (semiconductor); Context (archaeology); Probabilistic logic; Machine learning; Data mining; Artificial intelligence","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":[0.004444734,0.0008291416,0.0006746449,0.0008083166,0.0006082278,0.001585219,0.001355401,0.001065403,0.003038341],"category_scores_gemma":[0.008452127,0.0007508575,0.001091856,0.0004594043,0.000880311,0.001722131,0.001848051,0.001719278,0.0004359328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335114,"about_ca_system_score_gemma":0.002008277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00354919,"about_ca_topic_score_gemma":0.004309854,"domain_scores_codex":[0.9967344,0.001472931,0.0002527088,0.0006446801,0.000719604,0.0001755774],"domain_scores_gemma":[0.9969472,0.00182228,0.0003202503,0.00021187,0.0005693653,0.0001289369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001695897,0.00008678744,0.002005423,0.0002052204,0.0001288009,0.0001997843,0.0002792869,0.8567449,0.004547903,0.07234271,0.001358134,0.06193143],"study_design_scores_gemma":[0.00002357623,0.00003808548,0.0001675263,0.00002560284,0.00003258957,0.0000528194,0.00002079534,0.973775,0.001873215,0.02099151,0.002984517,0.00001474091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003396773,0.00008338241,0.9945509,0.0001565842,0.00001642622,0.00006063747,0.00005748436,0.0001942971,0.001483507],"genre_scores_gemma":[0.3870063,0.0003696225,0.6087978,0.0002964718,0.00004062527,0.0005615301,0.0003179764,0.00009214882,0.002517541],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004444734,"threshold_uncertainty_score":0.02350628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09512982472463485,"score_gpt":0.3764585223365461,"score_spread":0.2813286976119113,"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."}}