{"id":"W3204328284","doi":"10.1142/s219456592150007x","title":"CHINESE FOREIGN TRANSACTIONS: WHAT GETS THEM IN TROUBLE?","year":2021,"lang":"en","type":"article","venue":"Global economy journal","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Internationalization; Database transaction; Business; Competition (biology); China; Divergence (linguistics); Politics; Industrial organization; Transaction cost; Ordered logit; International trade; Finance; Political science; Computer science","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":[0.0011232,0.0003283409,0.0004845682,0.001519614,0.001383998,0.004054844,0.0005114965,0.000722856,0.006819981],"category_scores_gemma":[0.005585037,0.0001974463,0.0002720742,0.003930218,0.002208363,0.005481541,0.001109019,0.001134975,0.000723018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002708929,"about_ca_system_score_gemma":0.002559114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06429439,"about_ca_topic_score_gemma":0.06075439,"domain_scores_codex":[0.9991105,0.0001388561,0.00006604585,0.0001243757,0.0002883037,0.0002717783],"domain_scores_gemma":[0.9968439,0.0005240008,0.001295437,0.0002241436,0.0006232561,0.0004892899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002106902,0.00007605353,0.8027633,0.00036292,0.0001142664,0.002380741,0.0362475,0.0008281429,0.001016278,0.02918647,0.01924548,0.1075683],"study_design_scores_gemma":[0.00001992827,0.0001158925,0.8246644,0.0005306358,0.0001021478,0.00130565,0.1132251,0.002852638,0.000875261,0.0126089,0.04358866,0.0001107756],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577644,0.002597844,0.0005837654,0.01675736,0.0001233265,0.00002506159,0.0005672993,0.00004221236,0.02153875],"genre_scores_gemma":[0.9961872,0.001194439,0.00009928674,0.000524544,0.00008805844,0.000005614504,0.0002127788,0.00001277599,0.001675274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06429439,"threshold_uncertainty_score":0.1278403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438088424532084,"score_gpt":0.2314345062786217,"score_spread":0.2170536220333008,"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."}}