{"id":"W2954288090","doi":"10.1016/j.jval.2019.04.958","title":"PIN88 INTERRUPTED TIME SERIES ANALYSIS OF UVGI TECHNOLOGY TO REDUCE INFECTION RATES IN A CANADIAN HEALTH REGION - AN ECONOMIC ANALYSIS","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Medical Device Sterilization and Disinfection","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia; University of British Columbia","funders":"","keywords":"Medicine; Context (archaeology); Interrupted Time Series Analysis; Infection control; Environmental health; Emergency medicine; Intensive care medicine; Geography; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003984817,0.0006010475,0.0009251261,0.002158493,0.0007317607,0.001798913,0.001714559,0.0008850173,0.002659209],"category_scores_gemma":[0.009038968,0.0004417973,0.002412257,0.004536726,0.0005870266,0.000403798,0.0007083943,0.001474236,0.0001243843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02449395,"about_ca_system_score_gemma":0.02281889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9758749,"about_ca_topic_score_gemma":0.9489084,"domain_scores_codex":[0.9968237,0.0006997384,0.0001651043,0.000279323,0.0009604591,0.001071735],"domain_scores_gemma":[0.9951985,0.00187523,0.0009983686,0.0002251874,0.001248474,0.0004542586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003885317,0.0006261739,0.8162507,0.000779758,0.005200901,0.0008792841,0.0004783396,0.1194774,0.001173972,0.01306157,0.007796417,0.03039009],"study_design_scores_gemma":[0.0002183599,0.000561648,0.869451,0.0001006173,0.00170279,0.0001018471,0.001187411,0.121324,0.0003273375,0.000638528,0.004298665,0.00008777638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719743,0.002782,0.002715387,0.001401258,0.00005076524,0.0002711674,0.01665775,0.00005111866,0.004096139],"genre_scores_gemma":[0.990651,0.0009824311,0.000876179,0.0001366888,0.00002188196,0.00007664777,0.004302914,0.000006309748,0.002945964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02449395,"threshold_uncertainty_score":0.1777169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01888173487831798,"score_gpt":0.320163552074493,"score_spread":0.3012818171961751,"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."}}