{"id":"W6901883283","doi":"10.60692/yhjx2-cfj26","title":"Dossiê - 3º Simpósio Brasileiro de Comunicação Científica – SBCC, 2012.","year":2012,"lang":"pt","type":"article","venue":"Greater South Information System","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Public policy; Statistical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003115057,0.0004374984,0.0004940999,0.001119595,0.0007276848,0.001529633,0.002634802,0.0004923494,0.0002312881],"category_scores_gemma":[0.0001454608,0.0003751072,0.0002258157,0.001691791,0.0002545837,0.005401147,0.001225807,0.0005387182,0.01254142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004738399,"about_ca_system_score_gemma":0.0002643506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002041823,"about_ca_topic_score_gemma":7.202582e-7,"domain_scores_codex":[0.9947397,0.0003676853,0.001211239,0.0004434908,0.001267633,0.001970286],"domain_scores_gemma":[0.9956847,0.00004392631,0.0006510121,0.002310626,0.0004162401,0.0008935326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001455011,0.0000875381,0.4739833,0.001493242,0.0002743722,0.00003909006,0.4218314,0.000137047,0.000031965,0.02516949,0.04831354,0.02849355],"study_design_scores_gemma":[0.006460125,0.000626962,0.4532553,0.001158898,0.0001257457,0.001612171,0.06515775,0.3020388,0.005285217,0.00003307448,0.1612392,0.00300678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4478392,0.0002565984,0.5228887,0.0007988842,0.006887957,0.001460554,0.0003126842,0.001404591,0.01815075],"genre_scores_gemma":[0.9949063,0.000001697498,0.001375787,0.0002623438,0.0002127883,0.00008133593,0.00002321045,0.00001811984,0.003118411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.547067,"threshold_uncertainty_score":0.9998701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07040882751930594,"score_gpt":0.2693035361323332,"score_spread":0.1988947086130273,"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."}}