{"id":"W2912881330","doi":"","title":"UMA ANÁLISE DA PROTEÇÃO INFORMACIONAL PARA O PATRIMÔNIO CULTURAL","year":2017,"lang":"pt","type":"article","venue":"XVIII ENCONTRO NACIONAL DE PESQUISA EM CIÊNCIA DA INFORMAÇÃO (XVIII ENANCIB)","topic":"Cultural, Media, and Literary Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Cultural heritage; Art; Law","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":[0.008974942,0.0007744284,0.0006242936,0.01026987,0.003129891,0.00684761,0.001026396,0.0008932069,0.01193142],"category_scores_gemma":[0.0337983,0.0003921435,0.0007470268,0.01365305,0.002096106,0.003342971,0.002813628,0.001626767,0.001812199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007368071,"about_ca_system_score_gemma":0.01232439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1338921,"about_ca_topic_score_gemma":0.17789,"domain_scores_codex":[0.9914628,0.002432327,0.0007239873,0.0008207079,0.003809345,0.0007507929],"domain_scores_gemma":[0.9367768,0.02975856,0.006529516,0.002612141,0.02297171,0.001351422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000553785,0.0002581128,0.3185276,0.005754295,0.0003384024,0.001287438,0.353165,0.0005695804,0.008946294,0.0136129,0.01799294,0.2789938],"study_design_scores_gemma":[0.00001856899,0.0002435782,0.5492265,0.002331409,0.0003483207,0.0006035156,0.2689919,0.001116518,0.005549591,0.002175854,0.169248,0.0001462787],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8812296,0.003366339,0.01047113,0.003201839,0.0002387056,0.001039032,0.01327541,0.0004174407,0.08676054],"genre_scores_gemma":[0.930821,0.003047354,0.01761959,0.0005789542,0.00007588029,0.0009837378,0.004961675,0.0001664503,0.0417453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1338921,"threshold_uncertainty_score":0.2662256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05055027181053343,"score_gpt":0.2919976529500946,"score_spread":0.2414473811395611,"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."}}