{"id":"W2883507006","doi":"10.1007/s12134-018-0604-y","title":"Ethnic Spatial Segmentation in Immigrant Destinations—Edmonton and Calgary","year":2018,"lang":"en","type":"article","venue":"Journal of International Migration and Integration / Revue de l integration et de la migration internationale","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Destinations; Immigration; Metropolitan area; Ethnic group; Geography; Settlement (finance); Population; White (mutation); Regional science; Sociology; Demography; Anthropology; Tourism; Archaeology; Business","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":[0.001046249,0.0003801987,0.0005878225,0.002874341,0.004357592,0.003379904,0.001558571,0.000636871,0.005379735],"category_scores_gemma":[0.001951808,0.000356025,0.0004368034,0.009078871,0.001386679,0.001042349,0.004000753,0.001023957,0.0004494054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01105644,"about_ca_system_score_gemma":0.00956606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.934051,"about_ca_topic_score_gemma":0.9863243,"domain_scores_codex":[0.9994969,0.00009507314,0.00001825399,0.00006842353,0.00006918843,0.0002521297],"domain_scores_gemma":[0.9988651,0.0001470821,0.0001623905,0.00006452048,0.0004083007,0.0003525846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006343389,0.0002272863,0.8396124,0.0001023479,0.0001356544,0.001317334,0.08965305,0.0006220406,0.0007418705,0.007252133,0.008699353,0.05100217],"study_design_scores_gemma":[0.00001379933,0.00002064344,0.9273204,0.0001044728,0.00001764446,0.00005916946,0.06811318,0.0001502037,0.00006945519,0.0001969577,0.00392031,0.00001380693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915837,0.0005914147,0.00005714449,0.00053551,0.00002086,0.00001875914,0.0004931063,0.000003348746,0.006696091],"genre_scores_gemma":[0.9894156,0.0005836525,0.0002255152,0.0001838606,0.00001124358,0.00002834323,0.001051993,0.00001666023,0.008483153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06594902,"threshold_uncertainty_score":0.1326748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.027759006926503,"score_gpt":0.3444918293352338,"score_spread":0.3167328224087308,"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."}}