{"id":"W2039989283","doi":"10.1016/j.aeue.2009.04.010","title":"Optimal equalization for reducing the impact of channel group delay distortion on high-speed backplane data transmission","year":2009,"lang":"en","type":"article","venue":"AEU - International Journal of Electronics and Communications","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Backplane; Channel (broadcasting); Equalization (audio); Computer science; Distortion (music); Data transmission; Transmission (telecommunications); Electronic engineering; Telecommunications; Computer network; Computer hardware; Engineering; Bandwidth (computing); Amplifier","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001525056,0.0003483396,0.0002656129,0.0002110229,0.0002979357,0.0004243111,0.0002432479,0.0004209442,0.002619113],"category_scores_gemma":[0.0008306503,0.0001937511,0.000164778,0.0002447363,0.0002544583,0.0005354589,0.0002613722,0.0003617388,0.0003625965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000318193,"about_ca_system_score_gemma":0.0006218378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001098449,"about_ca_topic_score_gemma":0.003555082,"domain_scores_codex":[0.9997535,0.0000437325,0.00001184769,0.00004639044,0.0000926408,0.00005195271],"domain_scores_gemma":[0.9997405,0.0001207262,0.00002660842,0.00002191849,0.00008067457,0.000009576153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001295097,0.0002224737,0.001117819,0.0001934893,0.00008803465,0.0001276006,0.0001361389,0.1121813,0.533044,0.01575212,0.002116274,0.3337257],"study_design_scores_gemma":[0.00008385729,0.0002111087,0.001583229,0.00003088095,0.00008092273,0.0001788486,0.00004546281,0.7718787,0.2187602,0.003770085,0.003350226,0.00002655375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1433022,0.0006752615,0.8494419,0.0002534518,0.0001326165,0.00002372242,0.00004843288,0.0005029338,0.005619566],"genre_scores_gemma":[0.8616471,0.0003468118,0.1334738,0.0000926079,0.000071519,0.00001833674,0.00005418731,0.0000424479,0.004253126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002619113,"threshold_uncertainty_score":0.008761823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03698093473862427,"score_gpt":0.3387498112388458,"score_spread":0.3017688765002215,"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."}}