{"id":"W3121940051","doi":"","title":"Niveaux annuels d'immigration et gains initiaux des immigrants au Canada","year":2014,"lang":"fr","type":"article","venue":"Direction des études analytiques : documents de recherche","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Political science; Humanities; Concurrence; Art","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00628594,0.0004637167,0.0004681055,0.000215279,0.0009330087,0.0003856327,0.0003952222,0.0007322008,0.0007721773],"category_scores_gemma":[0.001800566,0.0005079351,0.0002361739,0.001636943,0.0006147914,0.001386589,0.00006347831,0.0008758053,0.00003819927],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009976307,"about_ca_system_score_gemma":0.00362787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9477136,"about_ca_topic_score_gemma":0.9980851,"domain_scores_codex":[0.9905628,0.006514431,0.0006732564,0.0006034855,0.0007005219,0.0009454804],"domain_scores_gemma":[0.9971192,0.0009394168,0.0003893746,0.00034485,0.0007004385,0.0005067341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001267421,0.0007708137,0.09569269,0.0004807076,0.0008753081,0.00002738648,0.1008205,0.002844277,0.000729622,0.2946284,0.01054994,0.4924535],"study_design_scores_gemma":[0.0008705208,0.0003454337,0.05566749,0.0008766627,0.000449972,0.00002643496,0.02554314,0.02881571,0.0013294,0.02776244,0.8568896,0.001423184],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8160465,0.002343158,0.02164252,0.00662609,0.001257524,0.0005369451,0.00009032621,0.0002870583,0.1511699],"genre_scores_gemma":[0.9249842,0.02146043,0.004727943,0.002301868,0.0004823359,0.00005053786,0.00009474184,0.00006249567,0.04583547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8463396,"threshold_uncertainty_score":0.9997372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1245957224779373,"score_gpt":0.4146234467868178,"score_spread":0.2900277243088805,"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."}}