{"id":"W2473215124","doi":"10.25336/p64609","title":"Canada's Immigration Trends and Patterns","year":2016,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Immigration; Fertility; Population; Demography; Geography; Population growth; Demographic transition; Political science; Demographic economics; Sociology; Economics; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000143647,0.00004697542,0.00006659522,0.0001298173,0.0001985158,0.00001166558,0.00003364398,0.00003415106,0.00005040337],"category_scores_gemma":[0.0001198938,0.00003797771,0.000006829794,0.0001747559,0.00004459221,0.00009926496,0.000004676982,0.0000220337,7.075392e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009617232,"about_ca_system_score_gemma":0.0002814734,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9977092,"about_ca_topic_score_gemma":0.999999,"domain_scores_codex":[0.9994714,0.00005413432,0.0001082838,0.0001005035,0.000104523,0.0001611098],"domain_scores_gemma":[0.9997308,0.0000369753,0.00002978005,0.0000506475,0.0000442919,0.0001075004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001344365,0.000001480862,0.8369363,0.000003309101,0.000007132803,0.000004430976,0.007528841,0.000004546535,0.000002573798,0.03396972,0.004719547,0.1168208],"study_design_scores_gemma":[0.0001163139,0.000004367939,0.9235246,0.00002727615,0.000003308626,2.506371e-7,0.005330061,0.00007242261,6.839496e-7,0.0004269032,0.07040221,0.00009157824],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811254,0.0001967448,0.00002234914,0.01601379,0.000358392,0.00006503404,0.00005465465,0.00001065347,0.002153033],"genre_scores_gemma":[0.9970049,0.000346164,0.00001065863,0.0003258223,0.00006859878,0.000006861691,0.00001261284,0.000003176235,0.002221199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1167292,"threshold_uncertainty_score":0.2514873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02465095037202225,"score_gpt":0.3080228920495796,"score_spread":0.2833719416775574,"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."}}