{"id":"W3161632147","doi":"10.2196/27065","title":"Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"Medicine; Asthma; COPD; Psychological intervention; Exacerbation; Intensive care medicine; Disease management; Disease; Health care; Physical therapy; Nursing; Pathology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03332986,0.003428928,0.005071327,0.003635232,0.003157246,0.003347516,0.002980888,0.003427093,0.1289292],"category_scores_gemma":[0.09109917,0.002149711,0.008915347,0.005423257,0.001993838,0.00249132,0.003839477,0.006738406,0.01732033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007076288,"about_ca_system_score_gemma":0.02326684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006104785,"about_ca_topic_score_gemma":0.007175058,"domain_scores_codex":[0.9772221,0.01196462,0.004772862,0.001676142,0.002643868,0.001720406],"domain_scores_gemma":[0.9561787,0.01306392,0.005600391,0.008596154,0.01422318,0.002337573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.1335523,0.009773455,0.005246765,0.1229719,0.008059902,0.0008081507,0.002266238,0.01369873,0.002952337,0.02311492,0.4762282,0.2013271],"study_design_scores_gemma":[0.2667857,0.01415223,0.02007736,0.05861344,0.005188827,0.0003883456,0.00127783,0.01235953,0.005219319,0.03391264,0.5812203,0.0008044906],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.0008853825,0.0002545818,0.004632052,0.0004718441,0.0004284632,0.9772593,0.01360791,0.0002790454,0.002181504],"genre_scores_gemma":[0.0005684142,0.00005833534,0.002209536,0.000111484,0.0000138353,0.9961768,0.0006648614,0.00001511947,0.0001815622],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1289292,"threshold_uncertainty_score":0.4313112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1616319677282322,"score_gpt":0.5783275849351311,"score_spread":0.416695617206899,"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."}}