{"id":"W3126411626","doi":"10.37702/cobenge.2020.3206","title":"INDICADORES BIBLIOMÉTRICOS SOBRE EDUCAÇÃO EM ENGENHARIA EM DIFERENTES BASES DE DADOS","year":2020,"lang":"pt","type":"article","venue":"Proceedings of the XLVIII Brasilian Congress of Engineering Education","topic":"Business and Management Studies","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000760328,0.000465792,0.0007328005,0.001466252,0.0002242648,0.0004340692,0.002010184,0.0001722353,0.0001570179],"category_scores_gemma":[0.007668834,0.0003669614,0.0003024695,0.005442703,0.0001617471,0.0008322803,0.0008122936,0.0003502861,0.00001803162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000071121,"about_ca_system_score_gemma":0.0003740847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005798501,"about_ca_topic_score_gemma":0.000003166991,"domain_scores_codex":[0.9965972,0.00002548141,0.001069515,0.0006748604,0.00113135,0.0005015336],"domain_scores_gemma":[0.9964879,0.0003816808,0.00116469,0.0003499571,0.00135332,0.0002625223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003418004,0.002754765,0.4447529,0.01337974,0.001438427,0.000001812378,0.03778455,0.001910669,0.03293432,0.009910727,0.2326247,0.2221656],"study_design_scores_gemma":[0.002081353,0.0005432915,0.7246577,0.006832222,0.001420638,0.00001626748,0.07269026,0.06293753,0.1172734,0.001281231,0.008196746,0.002069377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815138,0.003321267,0.001047592,0.008504077,0.004160259,0.001002147,0.00007833866,0.0001043283,0.0002682186],"genre_scores_gemma":[0.9974661,0.0005089025,0.0006769956,0.0002979329,0.0002719081,0.00008104255,0.000004087359,0.00005422341,0.0006388417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2799048,"threshold_uncertainty_score":0.9998782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04250318111118741,"score_gpt":0.3017021942569846,"score_spread":0.2591990131457972,"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."}}