{"id":"W4386456981","doi":"10.32920/24085074.v1","title":"Foreign Direct Investment Inflows into China","year":2023,"lang":"en","type":"preprint","venue":"","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Foreign direct investment; Economics; China; Index (typography); Exchange rate; Investment (military); International economics; Panel data; Regression analysis; Variables; Econometrics; Monetary economics; Macroeconomics; Mathematics; Statistics; Geography; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003479351,0.0003487327,0.0002117462,0.001270794,0.0003498371,0.0011896,0.0001209063,0.0001621922,0.001901798],"category_scores_gemma":[0.0012526,0.0001138231,0.0002680708,0.002209423,0.0001790555,0.0005768536,0.0006196287,0.0003129841,0.0002041004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002243893,"about_ca_system_score_gemma":0.002572527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0873647,"about_ca_topic_score_gemma":0.06746404,"domain_scores_codex":[0.9997755,0.00001497547,0.00002062992,0.00003639433,0.00008640336,0.00006610859],"domain_scores_gemma":[0.9994496,0.00006279951,0.0001982765,0.00002361634,0.0001708972,0.00009488269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001006474,0.00006276912,0.9280782,0.0001792912,0.00008145758,0.0009378303,0.0009284941,0.006761919,0.001208544,0.006206403,0.005858042,0.04959635],"study_design_scores_gemma":[0.000009739358,0.00004327714,0.977754,0.00005312276,0.00004460166,0.0001346407,0.0006599696,0.004379572,0.0009698309,0.0004389187,0.01549872,0.00001365779],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853919,0.0007039279,0.0001283696,0.000677453,0.00004105765,0.000008108947,0.001709735,0.0000377243,0.01130158],"genre_scores_gemma":[0.9939653,0.0007406124,0.00006689414,0.00005105235,0.00002635243,0.000005881166,0.001285198,0.00000468243,0.003854128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0873647,"threshold_uncertainty_score":0.1737124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02832267270688174,"score_gpt":0.2469094282218071,"score_spread":0.2185867555149254,"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."}}