{"id":"W2138480974","doi":"","title":"Chinese agricultural reform, the WTO and FTA negotiations","year":2006,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Agency for International Development; International Development Research Centre","keywords":"China; Agriculture; Liberalization; International trade; Negotiation; Free trade; Industrialisation; Arable land; Economics; Agricultural productivity; International economics; Comparative advantage; Agricultural policy; Business; Political science; Market economy; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0008156656,0.0003292013,0.0003264249,0.001022357,0.002110332,0.002287392,0.0003236694,0.0007465535,0.003731158],"category_scores_gemma":[0.001939442,0.0001324245,0.0002914467,0.002276098,0.00258647,0.001092719,0.001332247,0.000908607,0.0002211215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01312947,"about_ca_system_score_gemma":0.01138867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1334719,"about_ca_topic_score_gemma":0.1295711,"domain_scores_codex":[0.9992582,0.00008979854,0.00002655447,0.00007930953,0.0002956736,0.000250457],"domain_scores_gemma":[0.9996046,0.00007628298,0.0001027458,0.00006707239,0.0001049434,0.00004430788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000327915,0.0000414151,0.03526528,0.0003625423,0.0001006451,0.0009677627,0.008212818,0.006781471,0.00165885,0.8535189,0.02238061,0.07038187],"study_design_scores_gemma":[0.0001269769,0.0001308625,0.288527,0.0002476629,0.0002479735,0.0003731515,0.006136691,0.00619788,0.00500436,0.1799226,0.5129682,0.0001165608],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7011663,0.007420708,0.002209303,0.0223736,0.0002172042,0.0001457692,0.001366017,0.0000887763,0.2650124],"genre_scores_gemma":[0.9773466,0.002276929,0.0003481348,0.000726349,0.0000648453,0.00003157792,0.0001825408,0.00001287819,0.01901009],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1334719,"threshold_uncertainty_score":0.2653899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02301055742193857,"score_gpt":0.2086902285041194,"score_spread":0.1856796710821809,"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."}}