{"id":"W2335715647","doi":"10.1364/ofc.2016.tu2f.4","title":"Programmable Multi-Ring Butterworth Filters with Automated Resonance and Coupling Tuning","year":2016,"lang":"en","type":"article","venue":"Optical Fiber Communication Conference","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Butterworth filter; Bandwidth (computing); Computer science; Optical filter; Fabrication; Electronic engineering; Crosstalk; Filter (signal processing); Low-pass filter; Materials science; Prototype filter; Optoelectronics; Engineering; Telecommunications; Computer vision","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":[0.0003804784,0.0005828261,0.0002466622,0.0004416045,0.0002700149,0.0003836007,0.0008021753,0.0004238256,0.001459792],"category_scores_gemma":[0.0006486875,0.000338123,0.0001914576,0.0002440876,0.0004407615,0.0005532572,0.0003355636,0.000351242,0.0006612546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004707537,"about_ca_system_score_gemma":0.0002664482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005306746,"about_ca_topic_score_gemma":0.001869067,"domain_scores_codex":[0.9995826,0.00004677261,0.00002354877,0.0001024993,0.0001994848,0.00004504826],"domain_scores_gemma":[0.999429,0.0001882534,0.0001438663,0.0001348649,0.00007909858,0.00002479007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001162746,0.00005409302,0.0002962056,0.00005235126,0.00001484641,0.00005979967,0.00006613163,0.004314564,0.9344628,0.001737978,0.0003553785,0.05846955],"study_design_scores_gemma":[0.00004741846,0.0002568973,0.0006920288,0.000006735908,0.0000167941,0.0001688307,0.00001158212,0.0682398,0.9248905,0.0005616416,0.005071429,0.00003633824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3635552,0.0004270494,0.6233847,0.0002035555,0.0001172989,0.00009529687,0.0001039304,0.004659229,0.007453747],"genre_scores_gemma":[0.6464682,0.0001163122,0.3493772,0.00008511596,0.00003349347,0.00007240651,0.00006021787,0.0002119471,0.003575066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001459792,"threshold_uncertainty_score":0.004883468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333129300748949,"score_gpt":0.2413848674498549,"score_spread":0.2180535744423654,"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."}}