{"id":"W2036504595","doi":"10.1109/ita.2007.4357612","title":"Multiuser Water-filling in the Presence of Crosstalk","year":2007,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":154,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optimization problem; Computer science; Mathematical optimization; Multiuser detection; Crosstalk; Digital subscriber line; Maximization; Transmission (telecommunications); Iterative method; Algorithm; Mathematics; Telecommunications; Electronic engineering; Code division multiple access; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003346617,0.00003424025,0.00004010881,0.00003309081,0.00001591,0.000006902735,0.0002111328,0.00001765131,0.00003175502],"category_scores_gemma":[0.00001141257,0.00001913356,0.00001440352,0.00007563067,0.00001731079,0.0000479326,0.00002540008,0.00006656693,0.00000829813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000516156,"about_ca_system_score_gemma":0.000001295737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006951089,"about_ca_topic_score_gemma":0.0002026237,"domain_scores_codex":[0.9996889,0.000007416422,0.0001225057,0.000030416,0.00004691838,0.0001038267],"domain_scores_gemma":[0.9996088,0.00008916733,0.000004453263,0.0002755991,0.00001218609,0.000009786239],"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":[0.00005290251,0.0006132817,0.05139136,0.000253008,0.00007202999,0.00003229867,0.04848548,0.149841,0.6949781,0.01276308,0.003388046,0.03812935],"study_design_scores_gemma":[0.000703621,0.00002973157,0.07711875,0.00006142014,0.000007215921,0.000006908874,0.002040142,0.128034,0.7192015,0.0005519703,0.07193547,0.0003092934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9687577,0.0001721512,0.009874618,0.00005129496,0.00003927683,0.00005913667,7.479412e-7,0.00003624941,0.02100877],"genre_scores_gemma":[0.9979154,0.00003538418,0.001909744,0.00001462395,0.000007856352,0.000002456077,0.000001449069,0.000004466508,0.0001085857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06854742,"threshold_uncertainty_score":0.0780244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0165824778201657,"score_gpt":0.2571925516228914,"score_spread":0.2406100738027257,"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."}}