{"id":"W3124036475","doi":"","title":"Agricultural Trade Policy Modelling: Insights from a Meta-Analysis of Doha Development Agenda Outcomes","year":2008,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computable general equilibrium; Econometrics; Economics; Partial equilibrium; Meta-analysis; Policy analysis; Welfare; Sample (material); Tariff; Variable (mathematics); General equilibrium theory; Public economics; Microeconomics; Mathematics; International trade; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.1179449,0.003107398,0.007184228,0.01051017,0.000562933,0.00502605,0.002575271,0.002484764,0.002788058],"category_scores_gemma":[0.2003653,0.001318544,0.03103265,0.00887071,0.001042568,0.003071075,0.002201665,0.003337634,0.0002461035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004557494,"about_ca_system_score_gemma":0.003297142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006906735,"about_ca_topic_score_gemma":0.007426267,"domain_scores_codex":[0.9244477,0.06592935,0.003968164,0.003042867,0.002218304,0.0003935538],"domain_scores_gemma":[0.7316046,0.2422564,0.007333746,0.01478535,0.003506295,0.0005136806],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00256306,0.0001487799,0.02648716,0.06100594,0.7573832,0.0004115841,0.0009098148,0.06454252,0.0007424205,0.01345973,0.003024214,0.06932157],"study_design_scores_gemma":[0.00123682,0.001237449,0.01995989,0.02680773,0.8162615,0.0004721084,0.0007533504,0.03758202,0.001904841,0.07497635,0.01852731,0.0002807166],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.08716294,0.6950791,0.1851138,0.01435657,0.001132923,0.001580922,0.009180802,0.0006151493,0.005777826],"genre_scores_gemma":[0.8211007,0.1059358,0.0643479,0.002472487,0.0003516036,0.001618727,0.00344938,0.000209271,0.0005140602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9928158,"threshold_uncertainty_score":0.6237596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1585907502709626,"score_gpt":0.3198071272058212,"score_spread":0.1612163769348586,"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."}}