{"id":"W1585299339","doi":"10.13025/22968","title":"Selecting Economic Immigrants: A Statistical Approach","year":2009,"lang":"en","type":"preprint","venue":"ARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway)","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Earnings; Human capital; Economics; Selection (genetic algorithm); Econometrics; Computer science; Geography; Economic growth; Finance; Artificial intelligence","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":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.003282834,0.0004599158,0.001130513,0.00113889,0.002623011,0.0001450082,0.002494975,0.000950381,0.0003432295],"category_scores_gemma":[0.0002277344,0.0006592978,0.0005644548,0.0009482845,0.002958005,0.0005320045,0.0008730062,0.001941807,0.00005870239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478896,"about_ca_system_score_gemma":0.003076475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09136204,"about_ca_topic_score_gemma":0.03479685,"domain_scores_codex":[0.9928596,0.002414431,0.0004932031,0.001286493,0.001826347,0.001119913],"domain_scores_gemma":[0.9955553,0.0005447781,0.0008080074,0.001027598,0.001374251,0.0006900618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.01023661,0.008648212,0.04520812,0.005784195,0.006373096,0.002955732,0.5193358,0.02384617,0.01154817,0.2145498,0.1161017,0.03541248],"study_design_scores_gemma":[0.01477079,0.003448852,0.09120365,0.003207235,0.002223014,0.00006765513,0.643952,0.1409875,0.001189727,0.006939704,0.08519008,0.006819771],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8429364,0.0004069411,0.01774054,0.001431242,0.0004938832,0.001804858,0.0004519695,0.0002882545,0.1344459],"genre_scores_gemma":[0.9732279,0.002143711,0.007913992,0.00001342469,0.0001576503,3.289981e-7,0.0001197908,0.00003739067,0.01638578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.20761,"threshold_uncertainty_score":0.9997554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509502648909302,"score_gpt":0.2939029142111178,"score_spread":0.2588078877220248,"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."}}