{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008496362,0.000511315,0.0007422079,0.0002413011,0.0003065369,0.0008869852,0.000651249,0.0008833754,0.000850372],"category_scores_gemma":[0.002317892,0.000392201,0.000447344,0.000372935,0.001551936,0.001392128,0.0009969643,0.0006709296,0.000183746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007256828,"about_ca_system_score_gemma":0.0006896507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001419539,"about_ca_topic_score_gemma":0.001074041,"domain_scores_codex":[0.9995859,0.0001793645,0.00001354228,0.00005747522,0.0001085607,0.00005514932],"domain_scores_gemma":[0.999071,0.0006662553,0.00009938641,0.0000579942,0.00007465161,0.00003069252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008651014,0.00002395987,0.0003347679,0.00007955116,0.00002517524,0.000276041,0.0001559376,0.9232411,0.01052898,0.04927858,0.0003931015,0.0155763],"study_design_scores_gemma":[0.000005510316,0.00001763508,0.0000488943,0.000004624046,0.000003535155,0.0000327855,0.00001488257,0.9882481,0.002403149,0.008842956,0.0003706513,0.000007442429],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03386779,0.0002443982,0.9626667,0.000124804,0.0000191063,0.00001702317,0.00001798612,0.00009566537,0.002946479],"genre_scores_gemma":[0.8377392,0.0004792005,0.1561446,0.0001086615,0.00003159,0.0000604105,0.00004048547,0.00007678747,0.005319066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001419539,"threshold_uncertainty_score":0.005265236,"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."}}