{"id":"W7101177695","doi":"","title":"Other Human Capital: Immigrant Earnings in Canada","year":2002,"lang":"en","type":"article","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Earnings; Immigration policy; Public policy; Human resources","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":[0.0006501529,0.0002896423,0.000377939,0.00236511,0.007451314,0.003495085,0.001164592,0.0007706232,0.01330727],"category_scores_gemma":[0.002818482,0.0001246346,0.0003215098,0.004679101,0.001099885,0.0008192105,0.001642122,0.001175185,0.0005288419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05771133,"about_ca_system_score_gemma":0.09883612,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.997687,"about_ca_topic_score_gemma":0.999009,"domain_scores_codex":[0.9990159,0.00004522529,0.00002574062,0.0000725876,0.0002715544,0.0005690486],"domain_scores_gemma":[0.9974561,0.0001160769,0.0002205926,0.00005209384,0.0009880221,0.001167198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004313784,0.000217628,0.788247,0.0001607856,0.0001133163,0.0009213021,0.008215206,0.002173888,0.0004292518,0.05267286,0.05400944,0.09240798],"study_design_scores_gemma":[0.00003873642,0.00005559049,0.8976333,0.0002889934,0.00008042786,0.0002252214,0.0176798,0.002382159,0.0005026895,0.003154625,0.0778723,0.00008631975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.924762,0.003162466,0.0001996851,0.01159515,0.0001641486,0.00004542598,0.006976143,0.0000442583,0.05305079],"genre_scores_gemma":[0.970074,0.001253306,0.0001452209,0.0003256499,0.00002187028,0.000007850426,0.001080967,0.0000139104,0.02707726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05771133,"threshold_uncertainty_score":0.418727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320173327025254,"score_gpt":0.2445828034018703,"score_spread":0.2313810701316177,"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."}}