{"id":"W2272316893","doi":"10.22004/ag.econ.198436","title":"Efecto sobre el comercio y bienestar de distintas estrategias tecnológicas para el arroz uruguayo.","year":2012,"lang":"es","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Risk Management Agency; Ontario Ministry of Food and Agriculture; Purdue University; Monash University; University of Cambridge; Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria; Economic Research Service; Foreign Agricultural Service; U.S. Department of Agriculture","keywords":"Humanities; Geography; Political science; Agricultural science; Art; Biology","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":[0.00277299,0.0007209108,0.0008539371,0.0005210059,0.0008354839,0.0018715,0.000752995,0.0005297607,0.001964095],"category_scores_gemma":[0.002110927,0.000312053,0.0007468082,0.0009320794,0.0006209346,0.001094561,0.001044613,0.0006659714,0.0002833866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004843164,"about_ca_system_score_gemma":0.002758947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1414199,"about_ca_topic_score_gemma":0.2313944,"domain_scores_codex":[0.9987348,0.0005757305,0.00006042768,0.0002732445,0.000176166,0.0001795606],"domain_scores_gemma":[0.9987503,0.0002432428,0.0002907883,0.0001123168,0.0004595798,0.0001437682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004570218,0.001084121,0.2775592,0.004316924,0.0007997837,0.001847235,0.01290166,0.04635765,0.4648983,0.01137387,0.001686298,0.1726047],"study_design_scores_gemma":[0.0002042408,0.007619783,0.8208451,0.0008439139,0.001383982,0.0006441298,0.02209852,0.04357457,0.05197995,0.004153315,0.04645683,0.0001956737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986153,0.002670075,0.005046614,0.0003728476,0.00003274225,0.0001239236,0.0002902206,0.00007783275,0.005232643],"genre_scores_gemma":[0.9888085,0.001521938,0.006781875,0.00006007586,0.000006028037,0.00009179294,0.000254724,0.00003080681,0.002444352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1414199,"threshold_uncertainty_score":0.2811936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03861921585871583,"score_gpt":0.2532975673527706,"score_spread":0.2146783514940548,"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."}}