{"id":"W4313450388","doi":"10.1101/2022.12.16.22283534","title":"Patient Flow in Congested Intensive Care Unit /Step-down Unit system: Premature Step-down or not?","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"The King's University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intensive care unit; Proxy (statistics); Medicine; Downstream (manufacturing); Upstream (networking); Medical emergency; Intensive care medicine; Operations management; Computer science; Economics; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004455589,0.0005300258,0.000674608,0.0006028411,0.0004382289,0.001059655,0.0006884449,0.0007055962,0.002447386],"category_scores_gemma":[0.01131995,0.0002175073,0.0003428349,0.0003313049,0.0008618532,0.0009424314,0.0006154833,0.000805431,0.0001229907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482019,"about_ca_system_score_gemma":0.001765875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0061872,"about_ca_topic_score_gemma":0.003527662,"domain_scores_codex":[0.9979522,0.001133387,0.00006099137,0.0001767513,0.0001683839,0.0005083668],"domain_scores_gemma":[0.9877592,0.008584935,0.001482699,0.0003167878,0.0006723631,0.001184091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.004168345,0.001304066,0.06508066,0.0003208575,0.0002404269,0.000398893,0.0002074947,0.8823331,0.006878632,0.005660537,0.003507164,0.02989982],"study_design_scores_gemma":[0.0001562422,0.00101824,0.01761399,0.0000332432,0.00008125217,0.00006793296,0.0005644886,0.9727786,0.003379802,0.003893411,0.0003780089,0.00003482216],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984683,0.0001745899,0.01254363,0.0008353372,0.00005337345,0.0001088272,0.0001312203,0.00008975374,0.001380323],"genre_scores_gemma":[0.99787,0.0000348456,0.0018332,0.00006366572,0.000008770696,0.00001163177,0.00003560859,0.000004491392,0.0001376956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0061872,"threshold_uncertainty_score":0.02356362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08924355676118799,"score_gpt":0.3934373015120348,"score_spread":0.3041937447508468,"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."}}