{"id":"W2146476654","doi":"10.1080/00330124.2010.510087","title":"Modeling Spatial Accessibility of Immigrants to Culturally Diverse Family Physicians","year":2010,"lang":"en","type":"article","venue":"The Professional Geographer","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mainland; Immigration; Socioeconomic status; Geography; Catchment area; Metropolitan area; Gravity model of trade; Census; Multiculturalism; Spatial mismatch; Regional science; Demographic economics; Socioeconomics; Medicine; Environmental health; Business; Psychology; Sociology; Population; Cartography; Drainage basin; Economics","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":[0.0007249581,0.0004919471,0.0004553242,0.001077313,0.0006125248,0.001291625,0.0009687994,0.001101497,0.002548081],"category_scores_gemma":[0.003917112,0.0004928927,0.001010891,0.0009666244,0.0008002052,0.0008487101,0.001622651,0.0005709806,0.0002102306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002085649,"about_ca_system_score_gemma":0.001561435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1340407,"about_ca_topic_score_gemma":0.06442375,"domain_scores_codex":[0.9995785,0.0001755647,0.0000151246,0.00009637065,0.00002877775,0.0001056198],"domain_scores_gemma":[0.9988573,0.0006150709,0.0001966803,0.00006006122,0.0001520788,0.0001187915],"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":[0.00005687882,0.00008798792,0.03712043,0.00002530803,0.0000691654,0.0002938625,0.000364358,0.9460681,0.0002563412,0.01134138,0.0004814682,0.003834694],"study_design_scores_gemma":[0.00001664136,0.00002933189,0.005528336,0.000009051299,0.00002296313,0.00004988119,0.0003273021,0.9898428,0.00006312389,0.003598523,0.0005003982,0.00001157108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680383,0.0001611042,0.02712731,0.0004241934,0.00002400499,0.00004771815,0.0005652551,0.0001000756,0.003512074],"genre_scores_gemma":[0.9948015,0.0001023143,0.003254088,0.00001933162,0.00001297078,0.00003587954,0.000177745,0.00001231385,0.001583926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1340407,"threshold_uncertainty_score":0.2665209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312683797944372,"score_gpt":0.3236914444438169,"score_spread":0.3005646064643732,"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."}}