{"id":"W1606730456","doi":"10.1109/isplc.2015.7147610","title":"On PLC channel emulation via transmission line theory","year":2015,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Emulation; Electric power transmission; Solver; Channel (broadcasting); Power-line communication; Transmission line; Computer science; Computation; Electronic engineering; Conductor; Line (geometry); Transmission (telecommunications); Power (physics); Topology (electrical circuits); Algorithm; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001505721,0.00006334446,0.00005597839,0.0000496061,0.00002322285,0.000007312216,0.000093865,0.00003821349,0.00008742573],"category_scores_gemma":[0.00001119033,0.00005160483,0.00002134945,0.00007549522,0.00000614342,0.00006059653,0.000009287616,0.00007391844,0.0001084206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002063176,"about_ca_system_score_gemma":0.000005070804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003697159,"about_ca_topic_score_gemma":0.000001945591,"domain_scores_codex":[0.9996929,0.00002062441,0.00009300545,0.00005262211,0.00006418752,0.00007662301],"domain_scores_gemma":[0.9996151,0.00004035594,0.000006639888,0.0002425647,0.00002337897,0.00007200167],"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":[0.0001590027,0.0002968025,0.00002181042,0.00004320589,0.00005675724,0.000003001545,0.002579794,0.6637002,0.008881745,0.05433285,0.01836058,0.2515643],"study_design_scores_gemma":[0.0004347045,0.0000673419,0.0001653023,0.00002110462,0.000006746801,0.000001383672,0.0000331654,0.9428365,0.006133623,0.02766768,0.02249116,0.0001413453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03134526,0.0005629852,0.8916228,0.0003146455,0.0001767315,0.0001038862,0.000001702105,0.0004619361,0.07541008],"genre_scores_gemma":[0.9976258,0.00004178328,0.001392527,0.00006196347,0.00003684021,0.000005634088,0.0000168928,0.00001464513,0.0008039429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9662805,"threshold_uncertainty_score":0.2104384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871241429636719,"score_gpt":0.2517825924154355,"score_spread":0.2230701781190683,"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."}}