{"id":"W2294881683","doi":"","title":"Chinese Investment Emigration is Surging","year":2014,"lang":"en","type":"article","venue":"中国对外贸易：英文版","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Emigration; Real estate; Investment (military); Business; Geography; Economy; Political science; Economics; Finance","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":[0.0008376444,0.00009963454,0.0001315301,0.00005940743,0.0004838756,0.00009960221,0.0001553743,0.00008097338,0.0008191419],"category_scores_gemma":[0.000184371,0.00009174275,0.00006677792,0.0001906771,0.00008676139,0.0003156076,0.00002324408,0.0000746496,0.0003432247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007680032,"about_ca_system_score_gemma":0.00007536387,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01566764,"about_ca_topic_score_gemma":0.08439753,"domain_scores_codex":[0.9990039,0.0001399958,0.0001946634,0.0002083657,0.0002053327,0.0002477841],"domain_scores_gemma":[0.9994723,0.0000717838,0.00008832867,0.000185412,0.00005854201,0.0001236386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008818984,0.0001096725,0.3760203,0.00002839509,0.00003388849,0.000001121382,0.4705046,0.0000728318,0.0003383965,0.0631101,0.08114884,0.008623026],"study_design_scores_gemma":[0.0005802008,0.0000608335,0.1534956,0.00003148461,0.0000261577,0.000001064595,0.01442348,0.002219094,0.0005897586,0.0183749,0.8096496,0.000547817],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8832349,0.000103602,0.0005867243,0.002136069,0.0003950779,0.0001563231,0.000002363635,0.00008865442,0.1132963],"genre_scores_gemma":[0.9898278,0.00009740616,0.0002130669,0.002387265,0.0007844188,0.00001859189,0.00001264865,0.000008655694,0.006650154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7285007,"threshold_uncertainty_score":0.9908871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178422842885875,"score_gpt":0.3004263945546143,"score_spread":0.2825841102660269,"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."}}