{"id":"W2093405367","doi":"10.1109/tcsi.2007.905536","title":"Modeling and Design of Multilevel Bang–Bang CDRs in the Presence of ISI and Noise","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Jitter; Intersymbol interference; Noise (video); White noise; Computer science; Markov chain; Phase noise; Detector; Control theory (sociology); Algorithm; Electronic engineering; Statistics; Mathematics; Telecommunications; Engineering","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":[0.0005017706,0.0001060848,0.0001478229,0.00009773355,0.0001242789,0.00001863604,0.00007222776,0.00006125242,0.000001734544],"category_scores_gemma":[0.000003601793,0.00008434081,0.00001351506,0.0001016935,0.0001711566,0.0001123405,0.000002338567,0.0001106689,2.757111e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001119849,"about_ca_system_score_gemma":0.000003175906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002193219,"about_ca_topic_score_gemma":0.000009796349,"domain_scores_codex":[0.9993716,0.0000369362,0.0002510364,0.0001469295,0.00007700056,0.000116439],"domain_scores_gemma":[0.9994003,0.0003752144,0.0000344195,0.0001470962,0.0000145431,0.00002847493],"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":[0.0001012225,0.0003961611,0.0004400041,0.001170511,0.0001726806,0.000001355769,0.007738348,0.3736904,0.1632722,0.09494691,0.000005539654,0.3580647],"study_design_scores_gemma":[0.005722051,0.0008437323,0.003262548,0.002608398,0.0004741436,0.000385675,0.103278,0.7284209,0.06543029,0.08495153,0.002332276,0.002290425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2761779,0.001252668,0.7219688,0.000004558709,0.00003052159,0.0004155879,0.00004062441,0.00002557679,0.00008377487],"genre_scores_gemma":[0.9984152,0.0009924596,0.000410052,0.000006608597,0.000008157071,0.0001281597,9.709941e-7,0.000008895665,0.00002945291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7222373,"threshold_uncertainty_score":0.3439318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04162800476423593,"score_gpt":0.2717481614962163,"score_spread":0.2301201567319804,"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."}}