{"id":"W7095836986","doi":"","title":"Trends and Conditions in Census Metropolitan Areas Immigrants in Canada’s Census Metropolitan Areas","year":2015,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Immigration; American Community Survey; Range (aeronautics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003246757,0.0002242338,0.0003863838,0.0005592468,0.00006441351,0.00002740357,0.0001008629,0.00008647083,0.0001582228],"category_scores_gemma":[0.0004750485,0.0002078642,0.00004249993,0.0006196323,0.0000524754,0.000139744,0.00003735615,0.0001683059,0.000003912854],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004136601,"about_ca_system_score_gemma":0.0003537503,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9479131,"about_ca_topic_score_gemma":0.9926249,"domain_scores_codex":[0.998193,0.0001266192,0.0005926688,0.0002806526,0.0003743294,0.000432774],"domain_scores_gemma":[0.9989073,0.0002422943,0.0001370348,0.0002903668,0.0001189852,0.0003040364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004884587,0.0001854297,0.4631277,0.00004890257,0.00003342705,0.0000701842,0.0004108444,0.0000469449,0.00001194669,0.5000636,0.03439182,0.001560368],"study_design_scores_gemma":[0.002645425,0.00006094057,0.8794766,0.00007767668,0.00005505375,0.00005650008,0.01147345,0.007102956,0.00006882561,0.09580351,0.002656546,0.0005224866],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486461,0.0001679265,0.00006761109,0.002007006,0.0002137896,0.0002144202,0.0005196981,0.00005904581,0.04810437],"genre_scores_gemma":[0.9966226,0.000006983564,0.001927286,0.0001058827,0.00004148765,0.00001550487,0.0003025265,0.00002647288,0.0009512399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.416349,"threshold_uncertainty_score":0.9996864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06399851219161204,"score_gpt":0.3310872012110378,"score_spread":0.2670886890194257,"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."}}