{"id":"W2280137029","doi":"","title":"La mobilità intellettuale cinese: un´analisi delle destinazioni e della composizione del capitale umano qualificato","year":2010,"lang":"it","type":"article","venue":"RIVISTA GEOGRAFICA ITALIANA","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Destinations; Human capital; Phenomenon; Political science; Brain drain; Geography; Economic geography; Economy; Economic growth; Economics; Tourism","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003365558,0.0008864701,0.001011801,0.0003988779,0.002301335,0.0008717572,0.001751689,0.0008984923,0.009108837],"category_scores_gemma":[0.0009148904,0.0009426228,0.0006630406,0.001441971,0.002562513,0.0006797981,0.0003505862,0.001326843,0.003024598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002193638,"about_ca_system_score_gemma":0.0005071532,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0160876,"about_ca_topic_score_gemma":0.04964673,"domain_scores_codex":[0.9931015,0.001079637,0.001632022,0.001604719,0.001009098,0.001572975],"domain_scores_gemma":[0.9946054,0.001284303,0.0007069393,0.001645201,0.0006524561,0.001105709],"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":[0.0003595658,0.007790997,0.2276379,0.0009549608,0.001540785,0.0003033544,0.2415246,0.0005641484,0.007452627,0.1524516,0.343966,0.01545334],"study_design_scores_gemma":[0.00242411,0.0005782663,0.05709279,0.0003460138,0.0007015379,0.000116789,0.07052385,0.004323529,0.001516237,0.006773715,0.85169,0.003913164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634848,0.001410118,0.001091135,0.002749596,0.00113309,0.001128223,0.0002813812,0.0003410232,0.02838058],"genre_scores_gemma":[0.9768532,0.0006447104,0.001017566,0.0003482131,0.0009290643,0.0001071349,0.0002723362,0.0001186435,0.01970915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.507724,"threshold_uncertainty_score":0.9993024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714360317334941,"score_gpt":0.278888615269041,"score_spread":0.2617450120956916,"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."}}