{"id":"W4410608429","doi":"10.1186/s12913-025-12852-0","title":"Using interpretable survival analysis to assess hospital length of stay","year":2025,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; CARE Canada; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Science Foundation","keywords":"Health administration; Medicine; Health informatics; Nursing research; Metric (unit); Quality (philosophy); Duration (music); Health care; Event (particle physics); Operations management; Public health; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008499341,0.0001531419,0.0006344015,0.001518277,0.001664686,0.0000490838,0.0004789306,0.0002204808,0.0002864763],"category_scores_gemma":[0.0002606784,0.0001431864,0.00009392658,0.005932868,0.00004309622,0.0002094835,0.0003830189,0.0008352894,0.00004974315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006889164,"about_ca_system_score_gemma":0.004945383,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0177701,"about_ca_topic_score_gemma":0.01167623,"domain_scores_codex":[0.9925566,0.00386363,0.001200847,0.0005085999,0.0007894447,0.001080857],"domain_scores_gemma":[0.9951111,0.001334364,0.0002078927,0.0007283858,0.002204211,0.000414047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001958605,0.0003141488,0.9355221,0.006350813,0.0003466251,0.000001128151,0.01982225,0.02833934,0.0001835421,0.006860287,0.0001645991,0.001899246],"study_design_scores_gemma":[0.0008956245,0.0004338581,0.3317237,0.001899367,0.00009027588,1.007636e-7,0.06423923,0.5955287,0.00006997248,0.000186741,0.004636973,0.0002955511],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8411377,0.0003182977,0.1504065,0.001627213,0.0006732722,0.002245827,0.00008918924,0.00006068813,0.003441314],"genre_scores_gemma":[0.9554757,0.0001368176,0.0419598,0.0009626985,0.0001126412,0.0001508445,0.00008440586,0.00002400786,0.001093103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6037985,"threshold_uncertainty_score":0.999635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2541627028667069,"score_gpt":0.5992571363618344,"score_spread":0.3450944334951275,"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."}}