{"id":"W7100333451","doi":"","title":"You Can Take it with You! The Returns to Foreign Human Capital of Male Temporary Foreign Workers*","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Human capital; Work (physics); Foreign capital; Foreign born; Temporary work","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":[0.0004883035,0.0001337859,0.0001887958,0.0005697061,0.0008740853,0.001167618,0.0002215727,0.0003052258,0.01431157],"category_scores_gemma":[0.002995431,0.00006228057,0.0002365942,0.0005088222,0.000411298,0.0005055491,0.0005201909,0.0005603299,0.002394605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007965458,"about_ca_system_score_gemma":0.0007949667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1001416,"about_ca_topic_score_gemma":0.1654772,"domain_scores_codex":[0.9998255,0.00001691675,0.000004699646,0.00001355788,0.00005569724,0.00008376046],"domain_scores_gemma":[0.998541,0.0001459927,0.0003514592,0.00009311099,0.0002989636,0.000569355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002515786,0.0001059201,0.8141031,0.00004775688,0.0000734847,0.000331414,0.001785273,0.0002100515,0.0006122697,0.002744114,0.02099874,0.1587363],"study_design_scores_gemma":[0.00000834869,0.0001289287,0.9785594,0.0000431944,0.00002786219,0.0003397788,0.002684494,0.0001791096,0.0003329061,0.0006111573,0.01706872,0.00001595621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9710296,0.002018359,0.0003978962,0.004240898,0.0001417962,0.00001473413,0.001371998,0.00003684427,0.02074788],"genre_scores_gemma":[0.9755951,0.0007493679,0.0002230109,0.0004599666,0.00005898273,0.000007470645,0.000503546,0.00001246024,0.02239017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1001416,"threshold_uncertainty_score":0.1991174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01546342100382593,"score_gpt":0.2385856114350857,"score_spread":0.2231221904312597,"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."}}