{"id":"W2895808131","doi":"10.1109/group4.2018.8478737","title":"Subwavelength-Grating-Based 4-Channel Add-Drop Multiplexers in Silicon Photonics","year":2018,"lang":"en","type":"article","venue":"","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Multiplexer; Optical add-drop multiplexer; Wavelength-division multiplexing; Photonics; Grating; Silicon photonics; Materials science; Optoelectronics; Multiplexing; Optics; Photonic integrated circuit; Bandwidth (computing); Drop (telecommunication); Channel spacing; Wavelength; Diffraction grating; Insertion loss; Optical performance monitoring; Physics; Computer science; Telecommunications","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":[0.0001716584,0.0003510895,0.0003094867,0.0003036089,0.0001795321,0.0004127432,0.0006876591,0.0003107059,0.001093463],"category_scores_gemma":[0.0001189454,0.0002541554,0.0001872487,0.0001786514,0.0002623794,0.0005081238,0.0003497139,0.0002737572,0.0004775058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004143546,"about_ca_system_score_gemma":0.0001874709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003757132,"about_ca_topic_score_gemma":0.00110232,"domain_scores_codex":[0.9998404,0.00001588823,0.000009279303,0.00002528947,0.00008008743,0.00002900514],"domain_scores_gemma":[0.9999051,0.00002611529,0.00002993842,0.00001561931,0.00001281256,0.00001047024],"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":[0.0001026078,0.00006058958,0.0003798191,0.00005084129,0.00001090896,0.00008406874,0.00002487955,0.00355336,0.980231,0.002477548,0.0002917297,0.01273273],"study_design_scores_gemma":[0.00001965161,0.0002509669,0.0007454955,0.000003386582,0.00001361019,0.0001441622,0.000007334661,0.03849589,0.9563025,0.0005816552,0.003418833,0.00001663594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9450359,0.001208047,0.04679588,0.0001957437,0.0001220369,0.00005420614,0.0001641923,0.0008614119,0.005562714],"genre_scores_gemma":[0.9097408,0.0006181772,0.08418784,0.00007992733,0.00008986206,0.00005738965,0.0001315507,0.00003430404,0.005060032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001093463,"threshold_uncertainty_score":0.003658056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121223316388424,"score_gpt":0.2222454847730097,"score_spread":0.2110332516091255,"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."}}