{"id":"W1507973260","doi":"10.1109/mwscas.2003.1562504","title":"Automated network synthesis utilizing MAPLE","year":2006,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Frequency domain; Computer science; Maple; Equivalent circuit; Filter (signal processing); Network synthesis filters; Frequency response; Microwave; Network analysis; Set (abstract data type); Band-pass filter; Time domain; Domain (mathematical analysis); Electronic engineering; Mathematics; Engineering; Telecommunications; Electrical 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":[0.00007806235,0.00009264793,0.0001072395,0.00002522736,0.00005471716,0.00001995364,0.00007584794,0.00004971874,0.0007888529],"category_scores_gemma":[0.000009306184,0.00008513423,0.00003526361,0.0001459349,0.00001155457,0.00004676663,0.00001598595,0.00006509669,0.00007340548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002176298,"about_ca_system_score_gemma":0.000004415517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008804917,"about_ca_topic_score_gemma":0.0001098373,"domain_scores_codex":[0.9993959,0.00001826678,0.0001469166,0.0001062652,0.00007994521,0.0002527088],"domain_scores_gemma":[0.9996758,0.0001058206,0.000007845773,0.0001711813,0.000009879533,0.00002946947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002198832,0.0001066881,0.006734654,0.0001912452,0.00004687849,0.00001919203,0.00005904007,0.3085212,0.1183102,0.006147478,0.537998,0.02184351],"study_design_scores_gemma":[0.00009774414,0.00001818435,0.02051508,0.00004163259,0.00001299467,0.00000458508,0.000009253817,0.9187742,0.05210274,0.001415531,0.006807038,0.0002010134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.867259,0.0004140288,0.0005139298,0.00003874621,0.0001407745,0.00007568073,0.000001312873,0.003422637,0.1281338],"genre_scores_gemma":[0.9960563,0.000007934806,0.003452958,0.00001170688,0.0001079408,0.000011111,0.000004612515,0.00001651043,0.0003308783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.610253,"threshold_uncertainty_score":0.8637386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005933900510573054,"score_gpt":0.1931100249536752,"score_spread":0.1871761244431022,"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."}}