{"id":"W2941784673","doi":"10.22478/ufpb.1981-0695.2018v13n2.43329","title":"AVALIAÇÃO DA PRONTIDÃO DE DADOS PARA A ABERTURA DE DADOS DAS INSTITUIÇÕES PÚBLICAS BRASILEIRAS: CASO DE UMA INSTITUIÇÃO FINANCEIRA PÚBLICA BRASILEIRA","year":2018,"lang":"pt","type":"article","venue":"Pesquisa Brasileira em Ciência da Informação e Biblioteconomia","topic":"Information Science and Libraries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Political science; Humanities; Business; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"category_scores_codex":[0.005531092,0.002933112,0.002688637,0.01011778,0.003968786,0.01507206,0.01033429,0.002407651,0.002300289],"category_scores_gemma":[0.001980376,0.003103602,0.001190435,0.0170067,0.003111747,0.03430565,0.003031185,0.00303848,0.00607002],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002437284,"about_ca_system_score_gemma":0.01264371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001816258,"about_ca_topic_score_gemma":0.0008954284,"domain_scores_codex":[0.9826242,0.0005974482,0.005092746,0.002959435,0.00212887,0.006597328],"domain_scores_gemma":[0.9862323,0.0009072753,0.003354455,0.005185769,0.00139821,0.002922032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001702936,0.001654348,0.318926,0.001860497,0.001255293,0.0005769515,0.1641748,0.003396065,0.002528145,0.06784695,0.159258,0.27682],"study_design_scores_gemma":[0.007406039,0.002549749,0.3768247,0.001502917,0.0003672065,0.002876921,0.006416608,0.4084521,0.01393365,0.0007569434,0.1715997,0.007313562],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7820542,0.0008212212,0.1859886,0.001740862,0.004258158,0.003433546,0.0006600857,0.002007254,0.01903606],"genre_scores_gemma":[0.95766,0.0003400144,0.01856277,0.01750064,0.002034592,0.0006514405,0.000252126,0.0002429934,0.002755427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.405056,"threshold_uncertainty_score":0.9996012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0565637279976079,"score_gpt":0.3202097049953183,"score_spread":0.2636459769977104,"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."}}