{"id":"W4240651050","doi":"10.32920/ryerson.14648310","title":"Demographic changes and formation of ethnic enclaves","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Ethnic group; Geography; Population; Neighbourhood (mathematics); Economic geography; Demographic economics; Demography; Socioeconomics; Political science; Sociology; 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":[0.0002811854,0.00007868759,0.0001187088,0.0008512322,0.0009394604,0.0009823444,0.0002555039,0.0001262072,0.004089283],"category_scores_gemma":[0.001433695,0.000087509,0.0001084707,0.001250484,0.0006062519,0.0004770022,0.0008291565,0.000246917,0.0002967007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002028212,"about_ca_system_score_gemma":0.0009838186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2867313,"about_ca_topic_score_gemma":0.4480746,"domain_scores_codex":[0.9997543,0.00005266349,0.00001762014,0.00004048245,0.00004244001,0.00009248576],"domain_scores_gemma":[0.9991326,0.00004769065,0.000340051,0.0000478345,0.0001859607,0.0002459023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006111087,0.000018639,0.9690179,0.00003186917,0.00002643222,0.000232618,0.01405613,0.0002773812,0.0005307018,0.002491653,0.0008702201,0.01238541],"study_design_scores_gemma":[5.476244e-7,0.000007299292,0.9911879,0.000009219658,0.00000230393,0.00004301975,0.006060347,0.00006906947,0.00005954524,0.00006171058,0.002496344,0.000002625776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954458,0.000220441,0.00004284695,0.0001670935,0.000004257504,0.00000410533,0.000322481,0.000003095871,0.003789859],"genre_scores_gemma":[0.9986627,0.0001507092,0.00002267608,0.000006179074,0.000002396053,0.000001817899,0.0001900522,0.00000166014,0.0009617627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2867313,"threshold_uncertainty_score":0.5701247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08058506695710742,"score_gpt":0.3376849476981207,"score_spread":0.2570998807410133,"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."}}