{"id":"W2129973281","doi":"10.1186/1476-072x-5-43","title":"Defining rational hospital catchments for non-urban areas based on travel-time.","year":2006,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":210,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Rationalization (economics); Health geography; Rural area; Business; Health care; Population; Service (business); Location-allocation; Geographic information system; Health informatics; Geography; Environmental planning; Environmental health; Health policy; Medicine; Economic growth; International health; Marketing; Cartography; Economics","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":[0.001221227,0.0004154975,0.0003059918,0.001158491,0.0004247125,0.001516929,0.0009981229,0.0005399076,0.004155085],"category_scores_gemma":[0.005895449,0.0002275219,0.0005652695,0.001754996,0.0006316379,0.001275135,0.001242954,0.000463851,0.000291214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002492498,"about_ca_system_score_gemma":0.001905566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02707492,"about_ca_topic_score_gemma":0.02935736,"domain_scores_codex":[0.9993169,0.0003143463,0.00003902312,0.0001053075,0.0001129526,0.0001114685],"domain_scores_gemma":[0.9986192,0.0006658063,0.0002531439,0.0000841475,0.0002604337,0.0001172594],"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":[0.0001327423,0.0001019721,0.06862274,0.0001295289,0.00004859234,0.0002504466,0.0009822604,0.8395941,0.0008248971,0.06526036,0.002901183,0.02115116],"study_design_scores_gemma":[0.0000380168,0.00006274968,0.01602466,0.00003675299,0.00002947429,0.0001862216,0.001332828,0.9452521,0.0005906676,0.03051172,0.005911576,0.00002316342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.573868,0.0002550414,0.4086633,0.0008947675,0.00002922458,0.0008985386,0.002488628,0.0004112803,0.01249126],"genre_scores_gemma":[0.9406174,0.00008928665,0.05662815,0.00002274395,0.000005838406,0.0003728231,0.0007724412,0.00003740368,0.001453733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02707492,"threshold_uncertainty_score":0.05383468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03631430863341311,"score_gpt":0.3685921031486009,"score_spread":0.3322777945151878,"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."}}