{"id":"W3147282455","doi":"","title":"Annual Levels of Immigration and Immigrant Entry Earnings in Canada","year":2014,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Earnings; Demographic economics; Competition (biology); Immigration policy; Labour economics; Economics; Earnings growth; Political science","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":[0.0004969548,0.0001649772,0.0002427572,0.0009407153,0.002326383,0.001690843,0.0006922375,0.0003259404,0.003540102],"category_scores_gemma":[0.002424192,0.0001243545,0.0003128779,0.001355466,0.0007095811,0.0003284865,0.001107445,0.0008424894,0.0002747712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01851553,"about_ca_system_score_gemma":0.01973393,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9896025,"about_ca_topic_score_gemma":0.9951771,"domain_scores_codex":[0.9994811,0.00002650468,0.00001805491,0.00004685081,0.000159117,0.0002683505],"domain_scores_gemma":[0.9976397,0.000185507,0.0004149183,0.0000660033,0.0008017042,0.000892178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002023161,0.00009232191,0.9795944,0.00001596667,0.00003976199,0.0001677206,0.002841095,0.0006797644,0.0002752373,0.001170288,0.002206893,0.01271424],"study_design_scores_gemma":[0.000004148153,0.00001809975,0.9950929,0.0000241918,0.000008558291,0.00002321469,0.00286879,0.0003247751,0.00005645404,0.00005976803,0.001505509,0.00001369498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951095,0.0001623639,0.00002850639,0.0002948186,0.000008944938,0.000006278372,0.0006830865,0.000006545517,0.003699934],"genre_scores_gemma":[0.996199,0.0001395633,0.00004025602,0.0000298922,0.000003196588,0.00000242924,0.0005942386,0.00000362413,0.002987789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01851553,"threshold_uncertainty_score":0.1343402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009229122421722195,"score_gpt":0.213661912688018,"score_spread":0.2044327902662958,"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."}}