{"id":"W2329268949","doi":"10.5509/2008812217","title":"Immigration from China to Canada in the Age of Globalization: Issues of Brain Gain and Brain Loss","year":2008,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Immigration; China; Globalization; Political science; Demographic economics; Development economics; Economics; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009423771,0.0002391924,0.0002096287,0.001581965,0.007109204,0.002992285,0.000678963,0.0006039802,0.002281661],"category_scores_gemma":[0.003311738,0.00007059685,0.0002102925,0.003416216,0.0032553,0.001287103,0.001649666,0.001095221,0.0000668699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04233116,"about_ca_system_score_gemma":0.0510585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9784063,"about_ca_topic_score_gemma":0.9903948,"domain_scores_codex":[0.9994693,0.0000848889,0.00001460857,0.00003368112,0.0001114961,0.0002859271],"domain_scores_gemma":[0.9986622,0.0002062937,0.000206554,0.00003454438,0.0005047402,0.000385578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002446546,0.00007365189,0.6746649,0.0002170931,0.00008131252,0.002794111,0.07868976,0.001122294,0.0004138391,0.06673761,0.02083007,0.1541307],"study_design_scores_gemma":[0.00001335374,0.00005471735,0.7519004,0.0005308118,0.0000863501,0.0006674016,0.1987832,0.001096528,0.0003445444,0.00597281,0.04046671,0.00008318047],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327648,0.006219483,0.0001754022,0.03161725,0.0001088238,0.00001765813,0.0002659937,0.000006268544,0.02882438],"genre_scores_gemma":[0.9903722,0.005493442,0.0001179989,0.001443012,0.00004750049,0.000006543522,0.00006849313,0.000003208833,0.002447673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04233116,"threshold_uncertainty_score":0.3071355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251018052339113,"score_gpt":0.2531126627578639,"score_spread":0.2406024822344728,"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."}}