{"id":"W1973891858","doi":"10.1142/s021812660400191x","title":"NEW SAMPLING METHOD TO IMPROVE THE SFDR OF WIDE BANDWIDTH ADC DEDICATED TO NEXT GENERATION WIRELESS TRANSCEIVER","year":2004,"lang":"en","type":"article","venue":"Journal of Circuits Systems and Computers","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spurious-free dynamic range; Electronic engineering; Computer science; Channel (broadcasting); Spurious relationship; Bandwidth (computing); Successive approximation ADC; Dynamic range; Wireless; Transceiver; Converters; Sampling (signal processing); Engineering; Telecommunications; Electrical engineering; Capacitor","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":[0.0005791566,0.0001633436,0.0004028782,0.0001710639,0.0000679954,0.00009727647,0.0002204699,0.00007459889,0.000002052971],"category_scores_gemma":[0.00001072375,0.0001209961,0.0001082699,0.000237227,0.00001218928,0.0001622313,0.000007898193,0.0001777398,0.000002406823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008132985,"about_ca_system_score_gemma":0.00009184228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001356761,"about_ca_topic_score_gemma":0.00000872247,"domain_scores_codex":[0.9987254,0.00006917323,0.0005857588,0.0001338887,0.0002806754,0.0002050793],"domain_scores_gemma":[0.9991932,0.0001111892,0.0001537095,0.0001271196,0.0001395856,0.0002752309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001069144,0.00001441643,0.00003244494,0.0001087693,0.0002186477,0.00001285887,0.00236295,0.5176353,0.3651557,0.003517408,0.001346397,0.1095844],"study_design_scores_gemma":[0.03811763,0.0145937,0.02368369,0.01915989,0.004161317,0.008007784,0.01166512,0.355102,0.4334216,0.01407197,0.06910232,0.008913058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09245573,0.001057095,0.9052591,0.00008588063,0.0008373928,0.0002317909,0.00000321352,0.00002076799,0.00004899371],"genre_scores_gemma":[0.9973912,0.00003896397,0.001790203,0.0001801456,0.0005556426,0.000003069853,8.269893e-7,0.00002351166,0.00001648813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9049354,"threshold_uncertainty_score":0.4934077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03446991936076165,"score_gpt":0.2424049124761646,"score_spread":0.2079349931154029,"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."}}