{"id":"W3152957830","doi":"","title":"Skilled and Mobile: Survey Evidence of Immigration Preferences of AI Researchers.","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Socioeconomic Development in MENA","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Quarter (Canadian coin); Immigration policy; Political science; Immigration reform; Politics; Corporate governance; Public relations; Economics; Management; Geography; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003330331,0.000143962,0.0002539725,0.002096827,0.001586316,0.001592796,0.0004398513,0.0006717082,0.002852477],"category_scores_gemma":[0.01378693,0.0002275179,0.000202658,0.00252811,0.0009657154,0.00145687,0.002012885,0.0008829394,0.0006834402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006759347,"about_ca_system_score_gemma":0.0009771135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02252794,"about_ca_topic_score_gemma":0.0398698,"domain_scores_codex":[0.9984181,0.0007292689,0.000208889,0.000149202,0.00025197,0.0002425636],"domain_scores_gemma":[0.9814387,0.004305526,0.008701779,0.0005418666,0.001941934,0.003070248],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003549956,0.00005924721,0.9857785,0.00004418249,0.00002643019,0.00006950821,0.008805376,0.00001807932,0.00008932874,0.0002091451,0.001198922,0.003665969],"study_design_scores_gemma":[0.000005263521,0.0000734015,0.9548962,0.00006173232,0.00001179423,0.0001228388,0.04203689,0.00008878744,0.00004954965,0.0001250335,0.002513641,0.00001496741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971962,0.0002469619,0.00003676948,0.0006227574,0.00001042696,0.000009844111,0.0004718484,0.000001398851,0.001403685],"genre_scores_gemma":[0.9980106,0.0004007375,0.00008412878,0.0003935155,0.00001381832,0.00002726606,0.000402774,0.000002556958,0.00066459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9966697,"threshold_uncertainty_score":0.04479361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2450077050212985,"score_gpt":0.3038371800499102,"score_spread":0.05882947502861177,"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."}}