{"id":"W3125281483","doi":"10.1002/nav.20267/abstract","title":"Ambulance Location for Maximum Survival","year":2006,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Survival function; Service (business); Outcome (game theory); Monotonic function; Function (biology); Survival analysis; Emergency medical services; Location model; Computer science; Overall survival; Operations research; Medicine; Medical emergency; Engineering; Statistics; Business; Mathematics; Internal medicine","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":[0.002419852,0.001128421,0.001276424,0.0007728846,0.0007476844,0.001604383,0.001908647,0.001459454,0.007113732],"category_scores_gemma":[0.01081492,0.0006591056,0.001373277,0.0008397859,0.001510814,0.003479067,0.001483063,0.001651025,0.001247806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002876974,"about_ca_system_score_gemma":0.001439849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006834337,"about_ca_topic_score_gemma":0.005475464,"domain_scores_codex":[0.9985492,0.0006760198,0.00003615808,0.000330468,0.0001885431,0.0002196428],"domain_scores_gemma":[0.9946792,0.003492433,0.0008045931,0.0003312155,0.0004555236,0.0002369272],"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":[0.00004969416,0.00002022971,0.001439524,0.00004953027,0.00002687688,0.00006161297,0.0001509674,0.7989144,0.0002452004,0.1853595,0.002284146,0.01139824],"study_design_scores_gemma":[0.00002085951,0.00006225343,0.0007174677,0.00003634793,0.00002565377,0.00009858283,0.00005755283,0.8559286,0.0001473413,0.1387134,0.004165604,0.00002616191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06328822,0.0009480855,0.9187335,0.002203832,0.0001061511,0.00005676239,0.0005534832,0.0004202357,0.01368974],"genre_scores_gemma":[0.941407,0.001263016,0.04656921,0.0002556745,0.0001782813,0.0001687718,0.0004350933,0.0001583319,0.009564713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007113732,"threshold_uncertainty_score":0.02379781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241671405504998,"score_gpt":0.2213305962454452,"score_spread":0.2089138821903952,"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."}}