{"id":"W2109747629","doi":"10.1109/mwsym.2002.1011844","title":"Computer-aided tuning of microwave filters using fuzzy logic","year":2003,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Fuzzy logic; Microwave; Computer science; Filter (signal processing); Fuzzy electronics; Electronic engineering; Fuzzy control system; Algorithm; Engineering; Fuzzy classification; Artificial intelligence; Computer vision; Telecommunications","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":[0.0003296315,0.0001359579,0.0002626989,0.00008371309,0.00007163549,0.00007068602,0.0005084464,0.00005946599,0.000007638493],"category_scores_gemma":[0.00002046141,0.000110223,0.00009715985,0.0002784493,0.00004365623,0.0002131201,0.0001077214,0.00007172824,0.00002033633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003306687,"about_ca_system_score_gemma":0.00005932443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007193381,"about_ca_topic_score_gemma":0.000003057238,"domain_scores_codex":[0.9987729,0.0001376565,0.0003157557,0.0003040568,0.0001872597,0.0002824387],"domain_scores_gemma":[0.9991951,0.00008163949,0.0001367974,0.0004330798,0.00007778268,0.00007558546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004224442,0.00006907315,0.0008834069,0.00003404102,0.00004468879,0.00003141264,0.0004138493,0.002035658,0.07251918,0.9155995,0.0005332528,0.007831761],"study_design_scores_gemma":[0.004749185,0.0009516238,0.001955111,0.0002967218,0.00005649032,0.0007201481,0.0006731341,0.7175295,0.03591987,0.2316966,0.003586765,0.001864858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01729565,0.0001367554,0.9040516,0.00008127667,0.0004646282,0.0001231089,4.089327e-7,0.00008766315,0.07775889],"genre_scores_gemma":[0.7731745,0.000001717398,0.2262461,0.0003803109,0.00003288293,0.000001641198,3.117401e-7,0.000004443181,0.0001580009],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7558789,"threshold_uncertainty_score":0.4494762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428303399376007,"score_gpt":0.2355223507620746,"score_spread":0.2012393167683146,"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."}}