{"id":"W4376224452","doi":"10.1097/cce.0000000000000912","title":"Forecasting ICU Census by Combining Time Series and Survival Models","year":2023,"lang":"en","type":"article","venue":"Critical Care Explorations","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"The King's University; Western University","funders":"London Health Sciences Centre","keywords":"Census; Mean absolute percentage error; Observational study; Emergency medicine; Medicine; Computer science; Mean squared error; Statistics; Mathematics; Internal medicine; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005875775,0.0001031354,0.0001814119,0.0000505436,0.0002297816,0.00005471761,0.00002252083,0.00004961148,0.00003793837],"category_scores_gemma":[0.000374563,0.0000931594,0.00004223238,0.0001819293,0.00009411956,0.0001937027,0.00003925247,0.00007657864,0.00005544724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003470693,"about_ca_system_score_gemma":0.00002716186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008910749,"about_ca_topic_score_gemma":0.000008438504,"domain_scores_codex":[0.9992557,0.00002888826,0.0001473338,0.000199471,0.0001594276,0.0002092411],"domain_scores_gemma":[0.9991884,0.0003684574,0.00001024966,0.000106791,0.0001721755,0.0001539712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000634166,0.003144371,0.06532202,0.002586676,0.001026823,0.002754602,0.05721477,0.001820242,0.008696969,0.5352769,0.2674053,0.0541172],"study_design_scores_gemma":[0.02083386,0.01289232,0.02675822,0.003345896,0.004879037,0.0007397265,0.3278542,0.3746436,0.03124609,0.1540466,0.03809123,0.004669136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352087,0.003290466,0.001804023,0.03913521,0.0005635027,0.0008304956,0.0008382379,0.0009170184,0.01741232],"genre_scores_gemma":[0.998071,0.00005657605,0.0007335384,0.0001596875,0.0000723159,0.0001240987,0.0006438858,0.00002160863,0.0001172908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3812303,"threshold_uncertainty_score":0.379893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.250140240496637,"score_gpt":0.3762902388316335,"score_spread":0.1261499983349966,"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."}}