{"id":"W4283578244","doi":"10.2196/37913","title":"Impact of a Clinical Text–Based Fall Prediction Model on Preventing Extended Hospital Stays for Elderly Inpatients: Model Development and Performance Evaluation","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Science and Technology Agency","keywords":"Medicine; Propensity score matching; Psychological intervention; Covariate; Odds; Fall prevention; Predictive modelling; Emergency medicine; Logistic regression; Medical emergency; Injury prevention; Poison control; Computer science; Machine learning; Surgery; Internal medicine; Nursing","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":[0.01786275,0.002224698,0.00264914,0.001472839,0.0007044812,0.001888982,0.002045638,0.002052407,0.002348185],"category_scores_gemma":[0.019808,0.0006632048,0.002093509,0.0008228461,0.0005494109,0.001178132,0.001477477,0.002675244,0.0004376499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002749177,"about_ca_system_score_gemma":0.005021791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05116165,"about_ca_topic_score_gemma":0.0151746,"domain_scores_codex":[0.997595,0.001542209,0.0001778239,0.0003536764,0.000136106,0.0001952576],"domain_scores_gemma":[0.9766049,0.01988825,0.0007558208,0.0003460938,0.001988588,0.0004164256],"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":[0.00230714,0.001051863,0.02867686,0.000148758,0.0004735705,0.0001140932,0.00005876716,0.937681,0.0002382521,0.0004326556,0.001075987,0.02774117],"study_design_scores_gemma":[0.00008480167,0.0001761334,0.0009032119,0.00001472025,0.00007607998,0.000009405368,0.00001184853,0.9984269,0.00006658647,0.000182352,0.0000400136,0.000007920989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9026395,0.002277469,0.08559266,0.003067373,0.0002633026,0.0008976181,0.001559421,0.001350957,0.002351708],"genre_scores_gemma":[0.9636638,0.0004579244,0.03225769,0.0003747231,0.00008606763,0.0006687805,0.001625154,0.00003611733,0.0008298878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05116165,"threshold_uncertainty_score":0.1017277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06785536847149194,"score_gpt":0.4394991901487947,"score_spread":0.3716438216773028,"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."}}