{"id":"W4322504459","doi":"10.1177/01171968231153178","title":"Migration of high-skilled and STEM professionals from India: Addressing Global Compact for Migration objective 1","year":2022,"lang":"en","type":"article","venue":"Asian and Pacific migration journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Emigration; Inequality; Economic growth; Human migration; Geography; Political science; Development economics; Sociology; Economics; Population; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004666312,0.0001388239,0.0003521476,0.0001318672,0.000474598,0.0001421989,0.0000805186,0.00007677511,0.0001322695],"category_scores_gemma":[0.00002459286,0.0001502925,0.00008624907,0.0001353731,0.00004027866,0.0003758324,0.00002167531,0.0001680296,0.000003854836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001300688,"about_ca_system_score_gemma":0.00004842691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003378375,"about_ca_topic_score_gemma":0.0003380442,"domain_scores_codex":[0.998798,0.00006346793,0.0006456171,0.0002655546,0.00005737577,0.0001700226],"domain_scores_gemma":[0.9989669,0.000062146,0.0007198813,0.0001020796,0.00004445218,0.0001044962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006040636,0.0003733611,0.8809246,0.00007185167,0.0003841091,0.000005842834,0.01652571,0.0004802299,0.0002801606,0.06028888,0.03259106,0.007470092],"study_design_scores_gemma":[0.004219808,0.0007877495,0.8047207,0.0001072775,0.00006849863,0.0001590037,0.03824615,0.01034396,0.000391937,0.1024965,0.03779954,0.0006588958],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889489,0.001332381,0.001903521,0.004411394,0.0004955441,0.0003069963,0.001573498,0.00001011905,0.001017669],"genre_scores_gemma":[0.9983381,0.0003552615,0.0007045545,0.0001148241,0.0001341132,0.0000173469,0.0001884673,0.00000982451,0.0001374813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07620396,"threshold_uncertainty_score":0.6128751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04750151430740204,"score_gpt":0.2435137324020451,"score_spread":0.1960122180946431,"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."}}