{"id":"W2885912413","doi":"10.1109/access.2019.2914580","title":"Cable Diagnostics With Power Line Modems for Smart Grid Monitoring","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Electrical Fault Detection and Protection","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Smart grid; Computer science; Robustness (evolution); Grid; Real-time computing; Reflectometry; Power-line communication; Power (physics); Electrical engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002086432,0.0004772389,0.000256214,0.0004970995,0.0001381862,0.000323912,0.0004548879,0.0005406296,0.0009016744],"category_scores_gemma":[0.0009301605,0.0001265589,0.0002019143,0.0003526905,0.0002012934,0.0007091765,0.0003449578,0.0004902329,0.0003881022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002209653,"about_ca_system_score_gemma":0.0001806575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006668723,"about_ca_topic_score_gemma":0.001263577,"domain_scores_codex":[0.9997892,0.0000625578,0.000008869824,0.00004990036,0.00007257399,0.00001693641],"domain_scores_gemma":[0.9996604,0.0001331124,0.00006936445,0.00005909047,0.00006356008,0.00001460573],"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":[0.0003463334,0.0001291219,0.01031841,0.000165187,0.00005894496,0.000360661,0.0001810767,0.1472211,0.1183605,0.004567886,0.004073546,0.7142172],"study_design_scores_gemma":[0.00001814522,0.0001322343,0.002160933,0.00001447022,0.00001533125,0.0003624735,0.00004967741,0.955669,0.03425447,0.003503098,0.003804676,0.00001545655],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0485887,0.0002092491,0.9478068,0.0001565947,0.00002761238,0.00003791445,0.0000676991,0.001888075,0.001217341],"genre_scores_gemma":[0.7979759,0.0002009692,0.1996223,0.000136926,0.00006517648,0.00004220859,0.0001117144,0.00006437257,0.001780589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009016744,"threshold_uncertainty_score":0.003016412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631321275656396,"score_gpt":0.2652114762194023,"score_spread":0.2488982634628384,"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."}}