{"id":"W2101273286","doi":"10.1287/inte.1080.0405","title":"Fraser Health Uses Mathematical Programming to Plan Its Inpatient Hospital Network","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fraser Health; BC Cancer Agency","funders":"Fraser Health Authority","keywords":"Plan (archaeology); Process (computing); Population; Health care; Acute care; Operations management; Operations research; Capacity planning; Business; Computer science; Medicine; Engineering; Geography; Environmental health; Economics; Economic growth","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":[0.003239952,0.001513563,0.00112242,0.001263337,0.001022013,0.001960529,0.001332391,0.00120956,0.005086901],"category_scores_gemma":[0.005137137,0.001081815,0.001200207,0.001399712,0.0009198157,0.001127633,0.001180705,0.001713966,0.0004611896],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00434082,"about_ca_system_score_gemma":0.005731999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0473403,"about_ca_topic_score_gemma":0.04429186,"domain_scores_codex":[0.9989728,0.0005414685,0.00003865354,0.0001301085,0.0001478505,0.0001690418],"domain_scores_gemma":[0.9959918,0.003300724,0.0002459626,0.00006402847,0.0002444217,0.0001530096],"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":[0.00002574175,0.00002515665,0.000305831,0.00001995115,0.0000145036,0.00002575799,0.00002038095,0.9864476,0.00005472132,0.008601593,0.0006846718,0.00377407],"study_design_scores_gemma":[0.0000119202,0.00001499854,0.00003330369,0.000003847843,0.000003917894,0.000004170139,0.0000174531,0.9957886,0.00005620456,0.003636915,0.0004252045,0.000003523575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06052407,0.0003333656,0.9167714,0.00205368,0.00008474237,0.0006271779,0.001004575,0.0004649906,0.01813607],"genre_scores_gemma":[0.4654347,0.0006035003,0.5233564,0.0003206273,0.00006644784,0.001189666,0.0007899133,0.0001299852,0.00810873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9956592,"threshold_uncertainty_score":0.0941295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06127268751091639,"score_gpt":0.3935687067256145,"score_spread":0.3322960192146981,"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."}}