{"id":"W2126267511","doi":"10.1109/iscas.1993.393860","title":"Applications of 3D LCR networks in the design of 3D recursive filters","year":2002,"lang":"en","type":"article","venue":"1993 IEEE International Symposium on Circuits and Systems","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Planar; Modular design; Computer science; Filter (signal processing); Trajectory; Component (thermodynamics); Prototype filter; Network synthesis filters; Algorithm; Topology (electrical circuits); Filter design; Mathematics; Electronic engineering; Engineering; Computer vision; Programming language; Combinatorics; Physics","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":[0.0009428932,0.0001134179,0.0002016285,0.000128342,0.00005627406,0.00009631742,0.0007875187,0.00006268446,0.000006313461],"category_scores_gemma":[0.00002257423,0.00008519019,0.00004174172,0.000270587,0.00005963301,0.0001652546,0.00002745534,0.000123511,0.00000499615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003476131,"about_ca_system_score_gemma":0.00001085113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00011598,"about_ca_topic_score_gemma":0.000001517752,"domain_scores_codex":[0.9984381,0.0003374567,0.0004188095,0.000253174,0.0004069318,0.0001455164],"domain_scores_gemma":[0.9985878,0.0006729691,0.0002436117,0.0003163049,0.0001478005,0.00003151019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000886674,0.001316941,0.002653735,0.0003207642,0.0004698774,0.0001029588,0.0215057,0.3797986,0.0389241,0.1741364,0.009723824,0.3709585],"study_design_scores_gemma":[0.001283678,0.0003789008,0.0008844066,0.0004381239,0.00002555441,0.000139745,0.0001785195,0.9871389,0.001822722,0.0008997999,0.006451277,0.0003584147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001352337,0.0004374937,0.9908738,0.0004551497,0.0007551444,0.0004167703,0.000009327548,0.00001378853,0.005686252],"genre_scores_gemma":[0.9977775,0.000149303,0.001293556,0.0001787371,0.0002026463,0.00007909221,0.000002492,0.000006988638,0.0003096953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9964252,"threshold_uncertainty_score":0.3473955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04418617209323988,"score_gpt":0.2772256500958271,"score_spread":0.2330394780025872,"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."}}