{"id":"W2475938984","doi":"10.1109/pes.2007.385449","title":"A Power Line Signaling Based Scheme for Anti-islanding Protection of Distributed Generators: Part II: Field Test Results","year":2007,"lang":"en","type":"article","venue":"IEEE Power Engineering Society General Meeting","topic":"Islanding Detection in Power Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Islanding; Scheme (mathematics); Upstream (networking); SIGNAL (programming language); Line (geometry); Power (physics); Distributed generation; Computer science; Field (mathematics); Distributed power generation; Electronic engineering; Electric power system; Engineering; Electrical engineering; Telecommunications; Mathematics; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001841495,0.0004398737,0.0004798947,0.0001736873,0.0002603142,0.00006835443,0.0002103489,0.0003773027,0.00001011999],"category_scores_gemma":[0.0006667998,0.0004857848,0.0003976013,0.0006548597,0.00002452689,0.0001515599,0.00003221948,0.0004271067,0.00000233035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002534362,"about_ca_system_score_gemma":0.00003012601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001423386,"about_ca_topic_score_gemma":0.000002298944,"domain_scores_codex":[0.9973097,0.00002082788,0.001072442,0.0004403324,0.0003719017,0.0007847297],"domain_scores_gemma":[0.9985268,0.0005226642,0.0002272076,0.0003576856,0.0002283505,0.0001373442],"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":[0.00002744697,0.00002987608,0.0002388094,0.0002474566,0.0001091482,0.000002122295,0.0004730659,0.35763,0.6387089,0.00001010226,0.002478573,0.00004444304],"study_design_scores_gemma":[0.0008787354,0.0002235706,0.00003261657,0.0004069705,0.00002107561,0.000006618713,0.00006849856,0.3702841,0.6235002,0.000002146804,0.004169524,0.0004059889],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4459273,0.0001389115,0.5493292,0.0000398163,0.003108209,0.0004879357,0.000169552,0.0007027055,0.00009640207],"genre_scores_gemma":[0.9680558,0.000005429419,0.03050574,0.00003078715,0.001069483,0.00009828903,0.00005401468,0.0001352541,0.00004516948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5221285,"threshold_uncertainty_score":0.9997594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147733969786009,"score_gpt":0.221795882314459,"score_spread":0.2103185426165989,"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."}}