{"id":"W2462857461","doi":"","title":"USANDO AS LENTES DA ESTRATÉGIA PARA COMPREENDER OS DETERMINANTES DO DESEMPENHO EM PROJETOS DE PESQUISA E INOVAÇÃO AGROPECUÁRIA","year":2015,"lang":"pt","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Rural Development and Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Political science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03758374,0.0007513812,0.0006704691,0.002912214,0.001905643,0.008236923,0.001773402,0.001297951,0.02513481],"category_scores_gemma":[0.1161408,0.0005025733,0.001106751,0.00528084,0.002774592,0.006227858,0.005332013,0.002487717,0.002464851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004964286,"about_ca_system_score_gemma":0.02094515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03273059,"about_ca_topic_score_gemma":0.04846553,"domain_scores_codex":[0.9692855,0.01967208,0.001820692,0.002046633,0.004781781,0.002393238],"domain_scores_gemma":[0.8734895,0.08797083,0.009588121,0.008319075,0.01391175,0.006720725],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009577311,0.0009203465,0.3741426,0.003532537,0.0004941197,0.0003322374,0.01893876,0.003171341,0.003565877,0.0501493,0.02764442,0.5161508],"study_design_scores_gemma":[0.0002250214,0.001498818,0.7629235,0.007058123,0.001012778,0.0002307354,0.03736779,0.004306304,0.005463882,0.02856914,0.1511245,0.0002194506],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5525595,0.01872809,0.04102215,0.1203801,0.0009386188,0.002831398,0.01062092,0.001615736,0.2513035],"genre_scores_gemma":[0.9492341,0.003498702,0.03002996,0.002198262,0.000130773,0.001050814,0.001310397,0.0001982646,0.01234863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9624163,"threshold_uncertainty_score":0.1987642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03589999894405025,"score_gpt":0.2593759656462142,"score_spread":0.223475966702164,"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."}}