{"id":"W2120626011","doi":"10.1109/elinsl.1998.704723","title":"The importance of phase resolved partial discharge pattern recognition for on-line generator monitoring","year":2002,"lang":"en","type":"article","venue":"","topic":"High voltage insulation and dielectric phenomena","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Service de Recherche et d'EXpertise en Transformation des Produits Forestiers","funders":"","keywords":"Partial discharge; Line (geometry); Generator (circuit theory); Phase (matter); Computer science; Pattern recognition (psychology); Materials science; Electrical engineering; Artificial intelligence; Voltage; Engineering; Physics; Power (physics); Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002644986,0.00008465115,0.0001063149,0.00002425421,0.0001898958,0.00004267104,0.000112257,0.00002871597,0.0006178964],"category_scores_gemma":[0.0001320765,0.00005505903,0.00004231657,0.00008685741,0.00002821213,0.00009321552,0.00001223936,0.00003673831,0.00007845822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001587478,"about_ca_system_score_gemma":0.000008457784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006511173,"about_ca_topic_score_gemma":0.000006123196,"domain_scores_codex":[0.9991102,0.00002958234,0.0003139657,0.0001752347,0.0001623775,0.0002086788],"domain_scores_gemma":[0.9993863,0.000161049,0.0001281142,0.0001858012,0.00008136041,0.0000574092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00017829,0.000444034,0.001737892,0.00001758639,0.00001219212,0.000001399818,0.0002605123,0.00003558066,0.9279635,0.0006812828,0.002295878,0.06637186],"study_design_scores_gemma":[0.001649606,0.0003337739,0.0001100158,0.00001320203,0.00001007713,5.09427e-7,0.00003568078,0.02551039,0.9678237,0.0004469371,0.003932994,0.0001330653],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772474,0.0001008003,0.02087239,0.0003227229,0.0004521945,0.0002784421,0.00006233861,0.00004936754,0.0006143797],"genre_scores_gemma":[0.9982853,0.00003225532,0.0005789112,0.0001429123,0.0004557803,0.00008311628,0.00001000204,0.00001011552,0.0004016042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06623879,"threshold_uncertainty_score":0.6765532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0830177742091126,"score_gpt":0.3128233152737647,"score_spread":0.2298055410646521,"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."}}