{"id":"W6982326470","doi":"","title":"Immigrants sur le marché du travail canadien: qualité, gains et ségrégation","year":2015,"lang":"fr","type":"other","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Context (archaeology); Work (physics); Field (mathematics)","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":[0.002119728,0.0003077921,0.0005387571,0.002235369,0.004016824,0.00485774,0.001347515,0.001346132,0.01447104],"category_scores_gemma":[0.011298,0.0002492603,0.0004183651,0.005235612,0.001879258,0.002416118,0.003999689,0.002255972,0.00139659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005980982,"about_ca_system_score_gemma":0.009119555,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4212431,"about_ca_topic_score_gemma":0.4408433,"domain_scores_codex":[0.9983878,0.0003940164,0.00006444231,0.0001082136,0.000425514,0.0006200599],"domain_scores_gemma":[0.99551,0.0006947217,0.001074558,0.0001821242,0.001037864,0.001500736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004864867,0.0005267856,0.8141291,0.000170981,0.000139485,0.0005695324,0.07398463,0.0003262699,0.0002022678,0.01587629,0.01375162,0.0798366],"study_design_scores_gemma":[0.00002811309,0.0001509365,0.8578054,0.0003874727,0.00007888962,0.0001926658,0.1159368,0.0003042245,0.0001768901,0.003044592,0.02183802,0.00005618214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564865,0.004597192,0.0001194934,0.00893225,0.0001243618,0.00002972274,0.001050208,0.00001675384,0.0286434],"genre_scores_gemma":[0.9775673,0.001972639,0.0001014972,0.0002435345,0.00005717825,0.00003598704,0.0003900614,0.00001389601,0.01961789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5787569,"threshold_uncertainty_score":0.8375824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0268793530946647,"score_gpt":0.2444981452603734,"score_spread":0.2176187921657087,"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."}}