{"id":"W3127755419","doi":"10.51593/20190024","title":"Immigration Policy and the Global Competition for AI Talent","year":2020,"lang":"en","type":"report","venue":"","topic":"Information Systems Education and Curriculum Development","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Competition (biology); Immigration policy; Competition policy; Political science; International trade; Economic growth; Business; Economics; Law","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":[0.002111137,0.0002340811,0.0001422729,0.001420307,0.00326778,0.005625665,0.0003039979,0.001610955,0.008561847],"category_scores_gemma":[0.003883875,0.0001153891,0.000253776,0.002084166,0.001923868,0.002124769,0.002048729,0.002165669,0.0009757404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00674591,"about_ca_system_score_gemma":0.01352812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1192669,"about_ca_topic_score_gemma":0.1930636,"domain_scores_codex":[0.9978883,0.0005027888,0.00006774856,0.0001319669,0.0005939816,0.0008152665],"domain_scores_gemma":[0.997476,0.0006994256,0.0003919297,0.00007171754,0.0008136298,0.0005472941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001900728,0.0002209118,0.05815157,0.000470213,0.00003959981,0.0009023505,0.009136674,0.003161,0.001705942,0.5558678,0.1568366,0.2133173],"study_design_scores_gemma":[0.00002231679,0.0001415918,0.08954685,0.0008582518,0.00003507718,0.0003837227,0.0174576,0.001008776,0.0008708989,0.01702221,0.872598,0.00005480413],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1623045,0.008889643,0.0008529586,0.116995,0.001096954,0.0000400592,0.0004897545,0.00006757539,0.7092635],"genre_scores_gemma":[0.8123346,0.01871015,0.002084686,0.02636795,0.0006908274,0.00007900064,0.0007801598,0.00006387509,0.1388888],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1192669,"threshold_uncertainty_score":0.2371454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01933047203107117,"score_gpt":0.3101064419273794,"score_spread":0.2907759698963082,"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."}}