{"id":"W7111472472","doi":"","title":"Immigrant STEM Workers in the Canadian Economy: Skill Utilization and Earnings","year":2018,"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; New immigrants","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":[0.0006684376,0.0002574241,0.000224572,0.001791799,0.003219751,0.001509345,0.0007375543,0.0003911699,0.003621711],"category_scores_gemma":[0.001474469,0.0001322767,0.0003323412,0.003417924,0.0007138657,0.0004296789,0.0009083603,0.0006255184,0.0003420202],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01242387,"about_ca_system_score_gemma":0.01963226,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9910272,"about_ca_topic_score_gemma":0.9965863,"domain_scores_codex":[0.9995516,0.00002402994,0.00001714073,0.00003543989,0.0001382079,0.0002335627],"domain_scores_gemma":[0.9990211,0.00005156525,0.0001911115,0.00002535802,0.0003661681,0.0003446354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005572856,0.00004305047,0.9863672,0.00002088653,0.00002276364,0.0001369876,0.003101999,0.0001365542,0.0001613681,0.0004727611,0.001095807,0.008385004],"study_design_scores_gemma":[0.000003408877,0.00001475905,0.9878663,0.00002756848,0.00001049881,0.00003056562,0.009704137,0.00016198,0.00004858532,0.00004620455,0.002075711,0.00001031214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958222,0.0004792267,0.00002943041,0.0003478785,0.000008346642,0.00000820097,0.0007257317,0.000002615021,0.002576537],"genre_scores_gemma":[0.9957373,0.000668021,0.00005115712,0.00007908128,0.000005683858,0.000004301882,0.0006157212,0.000001846284,0.002836781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9875761,"threshold_uncertainty_score":0.09014195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418118473374132,"score_gpt":0.2456267192814789,"score_spread":0.2214455345477376,"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."}}