{"id":"W2902553559","doi":"10.3390/en11123344","title":"A PLC Channel Model for Home Area Networks","year":2018,"lang":"en","type":"article","venue":"Energies","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Mobile Communications Research Laboratory, Southeast University; Natural Sciences and Engineering Research Council of Canada; Southeast University","keywords":"Circuit breaker; Power-line communication; Interrupter; Electrical engineering; Engineering; Transformer; Network topology; Channel (broadcasting); Smart grid; Fault (geology); Power network; Electronic engineering; Computer science; Electric power system; Power (physics); Computer network; Voltage","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004506352,0.00007140517,0.00007510673,0.00003653009,0.00006751824,0.00001732834,0.0001690909,0.00003913114,0.00000863035],"category_scores_gemma":[0.000007211281,0.00006816602,0.0000342614,0.00006352891,0.00002866165,0.00006393342,0.00003880126,0.00004227122,0.00000629853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001185193,"about_ca_system_score_gemma":0.000005641051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003394448,"about_ca_topic_score_gemma":0.00003044065,"domain_scores_codex":[0.9996798,0.000003072989,0.00008064559,0.00006202534,0.00002910732,0.0001453158],"domain_scores_gemma":[0.9995982,0.00003010801,0.000009088621,0.0003020279,0.00003278832,0.00002780097],"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":[0.000003091476,0.000006043334,0.000003545394,0.000004471829,0.0000120359,7.04228e-8,0.0002304408,0.9831855,0.0001409995,0.001784339,0.01366802,0.0009613935],"study_design_scores_gemma":[0.000112553,0.00001282599,0.00004522826,0.000009277518,0.00000496575,4.386681e-7,0.00001991227,0.9851468,0.0003911963,0.001311988,0.01285125,0.00009358252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1802598,0.003298469,0.8062639,0.0001764104,0.0006333715,0.0001357324,0.0000245807,0.0006884065,0.008519336],"genre_scores_gemma":[0.9941681,0.0002789703,0.004378293,0.00004322603,0.0002019195,0.00006913458,0.0000149731,0.00002229566,0.0008230871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8139083,"threshold_uncertainty_score":0.2779729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257391830959442,"score_gpt":0.2328678959820069,"score_spread":0.2071287128860627,"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."}}