{"id":"W1957957393","doi":"10.11606/t.18.2010.tde-20102010-105622","title":"Metodologia para depuração off-line de parâmetros série e shunt de linhas de transmissão através de diversas amostras de medidas","year":2010,"lang":"pt","type":"dissertation","venue":"","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Physics; Humanities; Computer science; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005245631,0.000639629,0.0004773012,0.0006018454,0.0002928519,0.0008304568,0.0005311043,0.000542301,0.001822084],"category_scores_gemma":[0.001542784,0.000237735,0.0003978171,0.000475275,0.0001823769,0.0005696189,0.0002636927,0.0003952393,0.0004000731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004730855,"about_ca_system_score_gemma":0.0004268847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002506989,"about_ca_topic_score_gemma":0.002331121,"domain_scores_codex":[0.9996499,0.00006905807,0.00002604106,0.00007205489,0.0001575381,0.0000254127],"domain_scores_gemma":[0.9993526,0.0002230687,0.0001062009,0.00008386548,0.0002149355,0.00001935154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001658312,0.0002584303,0.02412233,0.000761608,0.000138136,0.0004207784,0.0008087698,0.3277479,0.3027713,0.001927833,0.001660728,0.3377239],"study_design_scores_gemma":[0.00006296929,0.001068148,0.01888081,0.00007716424,0.0001233688,0.0003870119,0.000461746,0.8063135,0.1644504,0.001491772,0.006616673,0.00006640919],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4267747,0.000483021,0.5654323,0.0002084125,0.00009230642,0.0001436268,0.0003784666,0.001893836,0.004593312],"genre_scores_gemma":[0.9523619,0.0002041556,0.04481086,0.00003518638,0.00001172511,0.00006313099,0.0001629144,0.0000718713,0.002278313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002506989,"threshold_uncertainty_score":0.006095469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0226735578979168,"score_gpt":0.2915493506970567,"score_spread":0.2688757927991399,"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."}}