{"id":"W3005767652","doi":"10.1093/migration/mnaa003","title":"International migration management in the age of artificial intelligence","year":2020,"lang":"en","type":"article","venue":"Migration Studies","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Identity (music); Politics; Face (sociological concept); Political science; Affect (linguistics); Sociology; Public relations; Political economy; Law; Social science","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":[0.000536274,0.00004274339,0.00006155187,0.00004237339,0.000122472,0.00003945886,0.000159842,0.00001522356,0.00001905305],"category_scores_gemma":[0.0003604611,0.00003267284,0.00002274514,0.000245616,0.00006891822,0.000149774,0.00003425077,0.00005660961,0.0000361952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000356296,"about_ca_system_score_gemma":0.000006519599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003540319,"about_ca_topic_score_gemma":0.007058916,"domain_scores_codex":[0.999194,0.0001472755,0.0001951208,0.0001032564,0.0002892485,0.00007108344],"domain_scores_gemma":[0.9997033,0.00008654317,0.00006992543,0.00005305685,0.00007720511,0.000009977825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001546839,0.0001639891,0.002574908,0.0001273998,0.0001423623,0.00004617911,0.6479014,0.0003342246,0.001646019,0.1493408,0.01504142,0.1825266],"study_design_scores_gemma":[0.0000525147,0.00008282275,0.002107254,0.00003055385,0.00005794549,2.413807e-7,0.5612369,0.000419644,0.0006732414,0.001865471,0.4333745,0.0000988916],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5638508,0.001306677,0.08066999,0.2795194,0.001660134,0.001852956,0.00003123032,0.000157048,0.0709517],"genre_scores_gemma":[0.9951311,0.002892609,0.0007048817,0.0008365202,0.0002765754,0.00002327747,0.00001235688,0.000002350293,0.0001203378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4312803,"threshold_uncertainty_score":0.3939041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2207794231395049,"score_gpt":0.3978444766928264,"score_spread":0.1770650535533215,"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."}}