{"id":"W2136451369","doi":"10.1371/journal.pone.0141113","title":"Spatial Access to Emergency Services in Low- and Middle-Income Countries: A GIS-Based Analysis","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Dalhousie University","funders":"","keywords":"Population; Catchment area; Preparedness; Geographic information system; Environmental health; Medicine; Health care; Kilometer; Business; Emergency medical services; Geography; Socioeconomics; Medical emergency; Economic growth; Drainage basin; Cartography; Economics; Transport engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001578018,0.0001608437,0.0005234902,0.0003928219,0.00004465198,0.00001838125,0.0001240154,0.00005873448,0.000309769],"category_scores_gemma":[0.00007787924,0.0001419889,0.0000646167,0.0009560604,0.00002775827,0.000107465,0.00008139178,0.00008772469,0.0000442983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006004164,"about_ca_system_score_gemma":0.0000515028,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00307766,"about_ca_topic_score_gemma":0.01927142,"domain_scores_codex":[0.9986083,0.00002692623,0.0003412936,0.0002981034,0.0004617576,0.000263625],"domain_scores_gemma":[0.9991239,0.00002140693,0.00005627852,0.0002594243,0.0002898786,0.0002491376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003170558,0.0004713716,0.9945109,0.001393617,0.000924838,0.00002451144,0.002086469,0.00003933668,0.00007982081,0.000005076068,0.00005272502,0.00009421542],"study_design_scores_gemma":[0.001389675,0.0002871133,0.9921283,0.0009337425,0.001615501,3.572887e-7,0.0004778267,0.001590721,0.001151228,0.00002960206,0.0001809173,0.0002149895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943705,0.0009236556,0.00005783312,0.002665205,0.00009198468,0.0003460992,0.00003030843,0.00005412548,0.001460351],"genre_scores_gemma":[0.9986618,0.0002282089,0.0002861175,0.0003864602,0.0001493923,0.0000652192,0.00002473887,0.00001534991,0.0001826742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01619376,"threshold_uncertainty_score":0.9986243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08656524061966804,"score_gpt":0.3072411339528597,"score_spread":0.2206758933331917,"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."}}