{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004279866,0.0006090146,0.0003560486,0.0002815685,0.0002436342,0.0006684077,0.0005706754,0.000443587,0.001399667],"category_scores_gemma":[0.0005353257,0.0003340502,0.00036917,0.000325051,0.0004018697,0.000828486,0.0003995929,0.0005454952,0.0008685174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005072832,"about_ca_system_score_gemma":0.0002550028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004262255,"about_ca_topic_score_gemma":0.0006810864,"domain_scores_codex":[0.999465,0.00008653219,0.00002656739,0.0001154142,0.0002100699,0.00009634712],"domain_scores_gemma":[0.9996612,0.0001029885,0.0001081596,0.00004618726,0.00006359591,0.00001777664],"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":[0.00009175934,0.00002687361,0.0003334425,0.00009771475,0.00001213408,0.00006601643,0.00005953886,0.000567095,0.9878433,0.002489915,0.0003158262,0.008096493],"study_design_scores_gemma":[0.000009973525,0.00006032556,0.0001689729,0.00000410541,0.000007632949,0.00007487374,0.000016102,0.002957818,0.9946063,0.0002008931,0.001886051,0.000007074218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7499594,0.002692569,0.2141783,0.0006458327,0.0004013743,0.0001915342,0.0002946875,0.001587452,0.03004876],"genre_scores_gemma":[0.9262052,0.001196933,0.06596038,0.0001656773,0.00006511839,0.00004490335,0.0001607669,0.0001463043,0.006054653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001399667,"threshold_uncertainty_score":0.004682362,"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."}}