{"id":"W1821525350","doi":"10.1111/cwe.12122","title":"Value, Structure and Spatial Distribution of Interprovincial Trade in China","year":2015,"lang":"en","type":"article","venue":"China & World Economy","topic":"Local Government Finance and Decentralization","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Stylized fact; China; Economics; Value (mathematics); Distribution (mathematics); International economics; International trade; Comparative advantage; Product (mathematics); Trade barrier; Economic geography; Business; Geography; Macroeconomics","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":[0.0004712554,0.0001611901,0.000217053,0.003508402,0.0004103413,0.0006758077,0.0002932115,0.0001195775,0.00187602],"category_scores_gemma":[0.001741925,0.0001363857,0.000240208,0.0060979,0.0005005076,0.0004936167,0.0006370039,0.0001640077,0.0001927105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394234,"about_ca_system_score_gemma":0.000857707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08889281,"about_ca_topic_score_gemma":0.1177118,"domain_scores_codex":[0.9996541,0.00004783678,0.0000307801,0.00009652271,0.00009923513,0.00007160957],"domain_scores_gemma":[0.9979784,0.000353416,0.0007863973,0.0002342532,0.0004666235,0.000181041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004230946,0.000009696881,0.9883852,0.00002682255,0.00006580417,0.0001294674,0.0004181913,0.002247731,0.0003710814,0.0009709281,0.0006204776,0.006712313],"study_design_scores_gemma":[0.000002663035,0.000007443375,0.9958263,0.000006651201,0.000009244658,0.00003055217,0.0002999095,0.002488021,0.0001357749,0.0002301979,0.000957049,0.000006250698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965209,0.0001321281,0.0001490616,0.00004474356,0.00000141203,0.000003216805,0.001878019,0.000009077522,0.001261531],"genre_scores_gemma":[0.9981488,0.00006711006,0.00008168372,0.000003751325,0.000002257996,0.000002577257,0.001386538,0.000001478289,0.0003058474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08889281,"threshold_uncertainty_score":0.1767508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007427545756263248,"score_gpt":0.2377608655152073,"score_spread":0.230333319758944,"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."}}