{"id":"W7045448381","doi":"","title":"Análise do mercado internacional de compensado","year":2016,"lang":"en","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Agricultural and Food Sciences","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Product (mathematics); German; Supply and demand; Indonesian; International market; Market price; Domestic market","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":[],"consensus_categories":[],"category_scores_codex":[0.002182302,0.0005197899,0.0006915837,0.003425594,0.001161536,0.002819422,0.001090681,0.0007775668,0.04549579],"category_scores_gemma":[0.01317318,0.0002375696,0.001439385,0.0026033,0.0006456834,0.002496272,0.001228428,0.001064943,0.002937287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002396437,"about_ca_system_score_gemma":0.001258729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01124962,"about_ca_topic_score_gemma":0.006945239,"domain_scores_codex":[0.9980521,0.0002787767,0.00009698446,0.000451447,0.0008461569,0.0002744922],"domain_scores_gemma":[0.9945577,0.00255168,0.0006591367,0.0007087479,0.001361674,0.0001610569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0008889936,0.000250009,0.131727,0.0009712331,0.0003567999,0.001863585,0.00179548,0.04049464,0.005162511,0.4465912,0.02035827,0.3495402],"study_design_scores_gemma":[0.0001847177,0.0005614874,0.1994805,0.0007823987,0.0005722441,0.004998484,0.005179034,0.3335029,0.0118187,0.1319618,0.3107471,0.0002105339],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5612454,0.006546868,0.1459328,0.002437483,0.000707172,0.0003312338,0.008167777,0.001955454,0.2726757],"genre_scores_gemma":[0.942497,0.001340755,0.02403408,0.00008058028,0.0001663227,0.0001216775,0.001901574,0.0002946945,0.02956334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04549579,"threshold_uncertainty_score":0.1521986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02439651368513197,"score_gpt":0.2294861142493973,"score_spread":0.2050896005642653,"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."}}