{"id":"W1583170243","doi":"10.1109/iccad.2004.1382658","title":"Dynamic range estimation for nonlinear systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Datapath; Computer science; Nonlinear system; Polynomial; Dynamic range; Range (aeronautics); Noise (video); Algorithm; Mathematics; Parallel computing; Artificial intelligence","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":[0.0003706444,0.0004423441,0.0004560648,0.0008374051,0.0002964312,0.0005577796,0.0003550216,0.0004416476,0.001167915],"category_scores_gemma":[0.003635626,0.0002323075,0.0002296757,0.0005892818,0.000453981,0.0009791669,0.0007160236,0.0006353792,0.0005115733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000367759,"about_ca_system_score_gemma":0.0002689268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007035244,"about_ca_topic_score_gemma":0.0004968989,"domain_scores_codex":[0.9995767,0.00009960974,0.00001817734,0.00009871287,0.0001803634,0.0000262963],"domain_scores_gemma":[0.9990653,0.0006340856,0.0001141446,0.00008051559,0.00009070049,0.00001522741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002177755,0.00004412995,0.001344796,0.0003401622,0.00005730091,0.0001966436,0.000231625,0.3099645,0.1301191,0.09455581,0.001806129,0.4611219],"study_design_scores_gemma":[0.000009667121,0.00004389727,0.0005295855,0.00002190075,0.00001319139,0.0002274332,0.00002180714,0.9421295,0.02756293,0.02425488,0.005153957,0.00003130099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01039154,0.0006819215,0.986609,0.00009945052,0.00001744151,0.00001239674,0.00002322151,0.000270891,0.001894198],"genre_scores_gemma":[0.611489,0.002422771,0.3810838,0.000129205,0.0001590756,0.00009986571,0.000205329,0.0001707251,0.004240172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001167915,"threshold_uncertainty_score":0.003907084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009859771334648633,"score_gpt":0.2564008649316756,"score_spread":0.2465410935970269,"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."}}