{"id":"W2907487643","doi":"10.1109/newcas.2018.8585488","title":"Maximal Flatness and Filters Transitional Between Butterworth and Inverse Chebyshev Ones","year":2018,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Academy of Finland","keywords":"Chebyshev filter; Butterworth filter; Mathematics; Flatness (cosmology); Chebyshev nodes; Network synthesis filters; Inverse; Control theory (sociology); Elliptic filter; Prototype filter; Filter design; Mathematical analysis; Applied mathematics; Filter (signal processing); Computer science; Physics; Engineering; Electronic engineering; Geometry","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":[0.00007652005,0.0001165359,0.0001321128,0.00005609223,0.00006605311,0.0000269297,0.00004130477,0.00006295075,0.0002241329],"category_scores_gemma":[0.000002393936,0.0001094083,0.00002166077,0.0000597535,0.0001343156,0.0001246361,0.000008177805,0.00007407059,0.00002981068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000962035,"about_ca_system_score_gemma":0.000006711691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000246882,"about_ca_topic_score_gemma":0.00003155625,"domain_scores_codex":[0.9994898,0.00001194691,0.0001080907,0.0001423849,0.00007870667,0.0001690351],"domain_scores_gemma":[0.9997737,0.00003183786,0.000005624568,0.00006614731,0.00001995925,0.0001027044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002675648,0.0001877716,0.2767088,0.001714738,0.002371461,0.0003184052,0.01960611,0.001175248,0.1749965,0.1090816,0.09369317,0.3198785],"study_design_scores_gemma":[0.006477509,0.001022475,0.8176787,0.0003327347,0.0006817731,0.0004106149,0.001645472,0.02705904,0.06969035,0.03617084,0.03494125,0.003889212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8082058,0.00008442722,0.1860813,0.00003143524,0.00006557621,0.00006858301,0.00002630858,0.0001458319,0.005290699],"genre_scores_gemma":[0.9991892,0.00002048242,0.0002340287,0.0001292892,0.0002139669,0.000003803602,0.00001714093,0.0000158702,0.0001762407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5409698,"threshold_uncertainty_score":0.4461539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01344744247634382,"score_gpt":0.1907228173925533,"score_spread":0.1772753749162095,"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."}}