{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002570756,0.0001969684,0.0002998269,0.00009859573,0.000811797,0.0001147333,0.00131346,0.0001230685,0.0000153477],"category_scores_gemma":[0.001875849,0.0001914373,0.0002080349,0.0002012064,0.00005609097,0.0004982712,0.0006484262,0.0004457763,0.000001051077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002446184,"about_ca_system_score_gemma":0.0005852458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001561075,"about_ca_topic_score_gemma":0.000005343743,"domain_scores_codex":[0.9971254,0.00005974152,0.0009710936,0.0002705527,0.0009234751,0.0006496652],"domain_scores_gemma":[0.9975848,0.0009543163,0.000419463,0.0004900775,0.0002409134,0.0003104376],"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":[0.0003052115,0.0008169357,0.006991651,0.01006068,0.0001722825,0.00000498997,0.1902992,0.2372908,0.00001543624,0.1075174,0.1028294,0.343696],"study_design_scores_gemma":[0.001019793,0.0007657373,0.00003577666,0.00003195233,0.000004844971,0.00001094787,0.00109631,0.96932,0.000007231165,0.002671092,0.024828,0.0002083395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05088015,0.00002351211,0.9401849,0.004698553,0.0008369494,0.002794801,0.0001418268,0.0002902774,0.0001490275],"genre_scores_gemma":[0.3307432,0.000001889123,0.6550136,0.006213252,0.0003754558,0.007315668,0.000161706,0.00003735374,0.0001378733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7320292,"threshold_uncertainty_score":0.7806585,"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."}}