{"id":"W4206906757","doi":"10.1787/11f80014-en","title":"Correlation between the share of immigrants from different regions of birth and living standards (median income and share of non-suitable housing) in Canadian cities, 2016","year":2021,"lang":"en","type":"other","venue":"International migration outlook","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Demographic economics; Geography; Standard of living; Demography; Socioeconomics; Economics; Sociology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007335736,0.0006368009,0.0004918381,0.003084403,0.002422105,0.001514363,0.002012342,0.0005950456,0.007528053],"category_scores_gemma":[0.003279641,0.0004066316,0.001419682,0.007611702,0.000730391,0.0006264816,0.00116388,0.001092903,0.0007542802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01824665,"about_ca_system_score_gemma":0.03356753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9963296,"about_ca_topic_score_gemma":0.9978471,"domain_scores_codex":[0.9991176,0.00003582018,0.00008792912,0.0001909155,0.000263868,0.0003039568],"domain_scores_gemma":[0.996049,0.000142804,0.0005328603,0.0001350813,0.00247535,0.0006648952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001169827,0.0000215755,0.982519,0.00006340461,0.0001267028,0.00005041379,0.0003651968,0.0003481055,0.00006256793,0.0003032016,0.01006153,0.005961302],"study_design_scores_gemma":[0.000003317416,0.000006407935,0.9972134,0.00002866829,0.00002865091,0.00002761502,0.0006877861,0.0001913715,0.00002647952,0.00002981901,0.001743271,0.00001314196],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8404334,0.004211319,0.0002612274,0.001344321,0.0001550618,0.00006270193,0.1401392,0.0001220981,0.01327073],"genre_scores_gemma":[0.9517874,0.002268331,0.0002593731,0.0001404014,0.00003598795,0.00003315062,0.03535938,0.00002887056,0.01008708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01824665,"threshold_uncertainty_score":0.1323893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813889293069769,"score_gpt":0.2755177530936128,"score_spread":0.2573788601629151,"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."}}