{"id":"W2169951754","doi":"10.1364/domo.2000.dtud23","title":"A new trapezoidal topology for designing diffractive optical elements with the iterative simulated quenching optimization","year":2000,"lang":"en","type":"article","venue":"Diffractive Optics and Micro-Optics","topic":"Optical Coatings and Gratings","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Quenching (fluorescence); Degrees of freedom (physics and chemistry); Topology (electrical circuits); Iterative method; Topology optimization; Computer science; Diffraction; Optics; Materials science; Electronic engineering; Mathematical optimization; Algorithm; Physics; Mathematics; Engineering; Finite element method; Electrical engineering; Thermodynamics","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":[0.0005065582,0.000736856,0.0005423692,0.0004435306,0.0002704124,0.0006206447,0.001015363,0.0007630737,0.00109244],"category_scores_gemma":[0.001400055,0.0004123264,0.0004639919,0.0004991374,0.000494948,0.0006672433,0.0005166489,0.0004608018,0.0003547585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004825734,"about_ca_system_score_gemma":0.00045656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005250676,"about_ca_topic_score_gemma":0.0007914896,"domain_scores_codex":[0.9997097,0.00007284169,0.00001883286,0.00004222239,0.0001357358,0.0000206251],"domain_scores_gemma":[0.9996264,0.0001332748,0.00004920809,0.00007946779,0.00008532213,0.00002625099],"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":[0.0001728065,0.00009564212,0.0009231558,0.0004411292,0.0000619407,0.0001881127,0.0002889605,0.643737,0.1869045,0.06353149,0.002116433,0.1015389],"study_design_scores_gemma":[0.00002808461,0.00008547839,0.00009679442,0.00001266478,0.00001301011,0.0001049824,0.00002065045,0.9687266,0.0220594,0.004011207,0.004815666,0.0000254535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02306289,0.0001657747,0.9728339,0.00005664373,0.000045185,0.00006818523,0.0000384128,0.0004920251,0.003237054],"genre_scores_gemma":[0.2412238,0.0001668889,0.7571632,0.00004979172,0.000009728505,0.0002216211,0.00007950619,0.0001290432,0.00095634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00109244,"threshold_uncertainty_score":0.00365454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010157858323343,"score_gpt":0.2558016811313082,"score_spread":0.2456438228079652,"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."}}