{"id":"W1763038965","doi":"10.3968/6970","title":"Empirical Research on Different Sources of FDI Technology Spillovers in Chinese Industrial Sector","year":2015,"lang":"en","type":"article","venue":"Higher education of social science","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Foreign direct investment; China; Latin Americans; Economic geography; Secondary sector of the economy; Manufacturing sector; International trade; Industrial technology; Production (economics); Business; Economics; Economy; International economics; Political science; Macroeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001484088,0.0003759387,0.0003516206,0.00389223,0.0005239779,0.001115633,0.0002439821,0.0003326296,0.00227375],"category_scores_gemma":[0.003277221,0.0001850683,0.0008307577,0.004659228,0.0004132933,0.001300252,0.0005349587,0.0004537286,0.0001414244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484282,"about_ca_system_score_gemma":0.001475585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0393461,"about_ca_topic_score_gemma":0.03085747,"domain_scores_codex":[0.9994736,0.00007926357,0.00004749819,0.00009611979,0.0001525057,0.0001509904],"domain_scores_gemma":[0.997475,0.001202391,0.0006484539,0.0001113252,0.0004196839,0.0001432377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009516808,0.00009287879,0.9295449,0.0004085296,0.0004407234,0.001296597,0.001982295,0.0129667,0.00145397,0.01417297,0.00125727,0.03628807],"study_design_scores_gemma":[0.00002343491,0.0000438558,0.9738007,0.0002103858,0.0004904715,0.0003638107,0.003886621,0.01329565,0.001426865,0.002573922,0.003848781,0.00003552195],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873876,0.002553544,0.001841471,0.0006085641,0.00001631952,0.00002999633,0.000848094,0.00001394815,0.00670035],"genre_scores_gemma":[0.9963158,0.001732102,0.0003176356,0.00003852875,0.00001973707,0.000009512891,0.0004865129,0.00000175301,0.001078483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0393461,"threshold_uncertainty_score":0.07823414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1422276806655409,"score_gpt":0.4077483119423422,"score_spread":0.2655206312768013,"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."}}