{"id":"W4239512703","doi":"10.1109/leos.2007.4382597","title":"Phase Matching using Bragg Reflection Waveguides","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Phase matching; Optics; Wavelength; Energy conversion efficiency; Harmonic; Reflection (computer programming); Phase (matter); Bragg's law; Second-harmonic generation; Frequency conversion; Power (physics); Optoelectronics; Materials science; Physics; Laser; Computer science; Electrical engineering; Engineering","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":[0.0002147204,0.0001878949,0.0001651206,0.0001534546,0.00009853298,0.00008106884,0.0001259956,0.0001041537,0.00004817393],"category_scores_gemma":[0.00005201723,0.0002062191,0.00003561909,0.000276144,0.00004319628,0.0004689353,0.00002563728,0.0002371085,0.00002857037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001499401,"about_ca_system_score_gemma":0.00001448004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008270143,"about_ca_topic_score_gemma":0.00000298426,"domain_scores_codex":[0.9989324,0.000001267619,0.0002763809,0.0002186725,0.000163682,0.0004075986],"domain_scores_gemma":[0.9995701,0.00002612189,0.00005216991,0.00007832677,0.0001612098,0.0001120925],"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":[0.00002682413,0.00003383867,0.0001691594,0.00009881494,0.00002314291,0.000008345661,0.003232196,0.0007145033,0.9659618,0.004160911,0.0001028775,0.02546754],"study_design_scores_gemma":[0.002094577,0.0001893429,0.000373327,0.0003853279,0.0000659895,0.0002884441,0.005792769,0.3024875,0.6669279,0.01507046,0.00514583,0.00117855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7819539,0.00004748621,0.2002407,0.00001472273,0.0002582941,0.0001089492,9.445572e-7,0.0005606322,0.0168144],"genre_scores_gemma":[0.9657329,0.00001782911,0.03385783,0.00003361377,0.0001722831,0.000003281408,0.000001733374,0.00004849015,0.0001320701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.301773,"threshold_uncertainty_score":0.840937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04598811771163713,"score_gpt":0.3167022757751923,"score_spread":0.2707141580635551,"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."}}