{"id":"W4388127722","doi":"10.1080/1369183x.2023.2270314","title":"Introduction: the intellectual migration analytics","year":2023,"lang":"en","type":"article","venue":"Journal of Ethnic and Migration Studies","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Science Foundation","keywords":"Intellectual capital; Agency (philosophy); Mobilities; Brain drain; Human capital; Sociology; Migration studies; Political science; Public relations; Social science; Economic growth; Gender studies; Economics; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002783347,0.0006440768,0.000361019,0.003741147,0.002132653,0.00778265,0.001272877,0.001800724,0.05997638],"category_scores_gemma":[0.01434515,0.0002344727,0.0007458594,0.005180689,0.002661738,0.007191387,0.004156942,0.003092536,0.01658174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001906808,"about_ca_system_score_gemma":0.003151836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004533378,"about_ca_topic_score_gemma":0.003096162,"domain_scores_codex":[0.998165,0.0006339898,0.0001339698,0.0003243793,0.0005912236,0.0001514151],"domain_scores_gemma":[0.9951954,0.002463201,0.0003147294,0.0006489865,0.001036391,0.0003412429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004218288,0.00004236344,0.003018933,0.0004316776,0.00001410993,0.0001585456,0.003942904,0.0006288243,0.0002527673,0.3907492,0.4149197,0.1857989],"study_design_scores_gemma":[0.000005434653,0.000009921805,0.001628027,0.0004775232,0.00000430623,0.0001408704,0.001392127,0.0008167209,0.0001707227,0.07801376,0.9173245,0.00001598315],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"editorial","genre_scores_codex":[0.01755758,0.02048343,0.08911907,0.1478709,0.01515021,0.0005390933,0.01974569,0.003831933,0.685702],"genre_scores_gemma":[0.3185579,0.03259223,0.1537775,0.02147165,0.02424427,0.00135873,0.02662501,0.004171788,0.4172009],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.05997638,"threshold_uncertainty_score":0.200641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09771751592037836,"score_gpt":0.392896484305282,"score_spread":0.2951789683849036,"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."}}