{"id":"W2940115145","doi":"10.1109/isplc.2019.8693385","title":"Fault Diagnostics with Legacy Power Line Modems","year":2019,"lang":"en","type":"article","venue":"","topic":"Electrical Fault Detection and Protection","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Precoding; Fault (geology); Broadband; Computer science; Power-line communication; MIMO; Noise (video); Channel (broadcasting); Line (geometry); Power (physics); Electronic engineering; Engineering; Telecommunications; Artificial intelligence","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":[0.00003132159,0.00008381938,0.00007815893,0.00004756583,0.00001982728,0.0000318239,0.00004039057,0.00006226194,0.0005220747],"category_scores_gemma":[0.00001436415,0.00006319147,0.00002040697,0.0002096392,0.000004856935,0.00012795,0.000004600746,0.0001759325,0.0005900527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002696172,"about_ca_system_score_gemma":0.000004419506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000017048,"about_ca_topic_score_gemma":0.00001150848,"domain_scores_codex":[0.9995869,0.000005929529,0.00008092021,0.00009240902,0.00009557665,0.0001382718],"domain_scores_gemma":[0.9997618,0.00004025127,0.00000717433,0.0001153458,0.00002773203,0.00004774916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001837795,0.0001579882,0.00225518,0.0001584345,0.0002229039,0.00002092436,0.0002990497,0.7884383,0.06181614,0.005667744,0.01179572,0.1289838],"study_design_scores_gemma":[0.001222942,0.001284422,0.001096372,0.00003331935,0.00001788004,0.00004540757,0.00005653139,0.7338425,0.1279432,0.0005246894,0.1333112,0.0006214898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6554316,0.0002233569,0.2285859,0.000169815,0.0005521931,0.000396509,0.000001566166,0.001274268,0.1133649],"genre_scores_gemma":[0.9961129,0.00005367143,0.0005454777,0.00011306,0.00004012176,0.00001163803,0.00000161644,0.00002091562,0.003100571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3406813,"threshold_uncertainty_score":0.758413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004148080476381835,"score_gpt":0.1918633819920571,"score_spread":0.1877153015156753,"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."}}