{"id":"W4214581630","doi":"10.2196/33044","title":"A Roadmap for Boosting Model Generalizability for Predicting Hospital Encounters for Asthma","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","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":"Generalizability theory; Asthma; Emergency department; Medicine; Health care; Predictive modelling; Medical emergency; Machine learning; Computer science; Nursing; Psychology","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":[0.02500664,0.002454791,0.003656445,0.002412658,0.001041115,0.002145501,0.003350161,0.002442586,0.002646666],"category_scores_gemma":[0.0534143,0.001165588,0.002532526,0.001528845,0.001068123,0.003596211,0.003263423,0.006879238,0.001389566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335992,"about_ca_system_score_gemma":0.002713346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01389381,"about_ca_topic_score_gemma":0.01391902,"domain_scores_codex":[0.9903926,0.006607807,0.0004262422,0.001376419,0.0008838752,0.0003131819],"domain_scores_gemma":[0.9696998,0.0206655,0.0008030193,0.004242923,0.003879821,0.0007089695],"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":[0.0006010708,0.0006328485,0.03758969,0.0003245215,0.0009318573,0.0002457376,0.0003555589,0.5498502,0.001850327,0.008513391,0.02269578,0.3764091],"study_design_scores_gemma":[0.00005486106,0.0001332724,0.001235458,0.00007322734,0.0001023675,0.0000371051,0.00004562805,0.9764797,0.0003952335,0.01850132,0.002915421,0.00002646616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05904782,0.01031938,0.9058909,0.01224909,0.0007674036,0.0006449792,0.001004325,0.005737598,0.004338407],"genre_scores_gemma":[0.5530495,0.003387064,0.4290116,0.005972828,0.001408414,0.0007363879,0.003267065,0.0008963426,0.002270773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02500664,"threshold_uncertainty_score":0.1322493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045177502912563,"score_gpt":0.3211856808417402,"score_spread":0.3007339058126145,"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."}}