{"id":"W6939184195","doi":"10.60692/c28nz-6d487","title":"Design of a silicon Mach–Zehnder modulator via deep learning and evolutionary algorithms","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Artificial neural network; Heuristic; Block (permutation group theory); Differential evolution; Evolutionary algorithm; Voltage; Bandwidth (computing); Deep learning; Boundary (topology)","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":[0.0002402765,0.0002905257,0.0002949068,0.0002128898,0.0001898213,0.0003387958,0.0004458737,0.0006206896,0.001464376],"category_scores_gemma":[0.0003526288,0.0002295527,0.0002780082,0.0001540644,0.0003274082,0.0002752038,0.000269519,0.0004072486,0.0001788132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006451529,"about_ca_system_score_gemma":0.0007613864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001384462,"about_ca_topic_score_gemma":0.00274064,"domain_scores_codex":[0.9999174,0.00001615372,0.000002929241,0.00001449433,0.0000330114,0.00001592814],"domain_scores_gemma":[0.999905,0.00003981354,0.0000173108,0.000006618791,0.00002284943,0.000008380734],"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":[0.00004485618,0.00004947869,0.0006731403,0.00005389446,0.0000324393,0.0000720386,0.00003098338,0.9363905,0.02126179,0.01110359,0.0005218668,0.0297654],"study_design_scores_gemma":[0.000004550903,0.00001265201,0.00003521701,0.000001908979,0.000002080823,0.000003877873,0.000001652181,0.9984462,0.0009167272,0.0003446689,0.0002293459,0.000001238848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1401053,0.0003636465,0.8418061,0.000469281,0.00005737071,0.00008525106,0.00004589573,0.0003765717,0.01669069],"genre_scores_gemma":[0.7844748,0.00009193961,0.2117824,0.0001009007,0.00001097267,0.0001267962,0.00003510851,0.00002865063,0.003348447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001464376,"threshold_uncertainty_score":0.004898787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01887310311190081,"score_gpt":0.1959029774996536,"score_spread":0.1770298743877528,"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."}}