{"id":"W2088576342","doi":"10.1109/tpwrd.2007.905566","title":"Evaluation of LV and MV Arc Parameters","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Electrical Fault Detection and Protection","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Arc (geometry); Computation; Electric arc; Voltage; Electrical engineering; Arc-fault circuit interrupter; Fault (geology); Circuit breaker; Electronic engineering; Computer science; Engineering; Reliability engineering; Algorithm; Mechanical engineering; Physics; Electrode; Short circuit","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006155793,0.0005719605,0.0005537564,0.002154813,0.0002060811,0.0007882433,0.000371338,0.0004650902,0.003018602],"category_scores_gemma":[0.003303682,0.0001275516,0.0002217187,0.001354079,0.0002627541,0.001283599,0.0004397484,0.0003366921,0.0007810445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005623204,"about_ca_system_score_gemma":0.0002235203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007367851,"about_ca_topic_score_gemma":0.0007527819,"domain_scores_codex":[0.9992224,0.0001545385,0.00005633047,0.0001147724,0.0004132472,0.00003875394],"domain_scores_gemma":[0.9980703,0.0007501984,0.00028575,0.0002258908,0.0006056463,0.00006219817],"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":[0.001319134,0.0001396321,0.04528178,0.0008081831,0.0001293548,0.0003232576,0.0005750509,0.1666051,0.1539649,0.007397607,0.002403287,0.6210527],"study_design_scores_gemma":[0.00006509011,0.001055085,0.06670406,0.0001259128,0.0001535355,0.001362565,0.0005844595,0.5244683,0.3818233,0.005135857,0.01839514,0.0001266511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4308651,0.001712472,0.5400873,0.00009923507,0.0000557115,0.0001890891,0.001384049,0.002897699,0.0227094],"genre_scores_gemma":[0.9796689,0.0002627817,0.01779923,0.00001002892,0.00001064282,0.00003084938,0.0003855825,0.0001525891,0.001679424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003018602,"threshold_uncertainty_score":0.01009816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02934169906973367,"score_gpt":0.2336339807143289,"score_spread":0.2042922816445953,"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."}}