{"id":"W2018978545","doi":"10.1109/lpt.2005.846570","title":"Refractive index sensor based on microstructured fiber Bragg grating","year":2005,"lang":"en","type":"article","venue":"IEEE Photonics Technology Letters","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":120,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Materials science; Fiber Bragg grating; Optics; PHOSFOS; Cladding (metalworking); Refractive index; Normalized frequency (unit); Grating; Graded-index fiber; Etching (microfabrication); Optical fiber; Fiber optic sensor; Optoelectronics; Stopband; Step-index profile; Layer (electronics); Wavelength; Physics; Composite material","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":[0.0001390078,0.0002310174,0.0003170974,0.0002353733,0.0001121164,0.0002325493,0.0004438531,0.0003157245,0.0003772074],"category_scores_gemma":[0.0002505496,0.0001927267,0.0001446635,0.0001647572,0.0002039593,0.0003836217,0.000219735,0.0001679937,0.0002044161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003315402,"about_ca_system_score_gemma":0.0002070209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007646361,"about_ca_topic_score_gemma":0.001584039,"domain_scores_codex":[0.999754,0.00002270636,0.000008476741,0.0000584201,0.0001400935,0.0000163956],"domain_scores_gemma":[0.9998085,0.00003513984,0.00005212823,0.00002148641,0.0000696389,0.00001321016],"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":[0.00004476083,0.00001030715,0.0005578276,0.0000570685,0.000007855602,0.00002825775,0.00001179879,0.0004468668,0.9893298,0.0002030321,0.00008964601,0.009212696],"study_design_scores_gemma":[0.00001526629,0.0002924997,0.006779179,0.000008281026,0.00002992824,0.0005052998,0.00001612395,0.02274067,0.9660763,0.000181309,0.003332087,0.00002296208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7764491,0.003533577,0.2117229,0.0002255304,0.0002380631,0.0001069057,0.0004094486,0.002060531,0.005253892],"genre_scores_gemma":[0.8279624,0.0008861041,0.1691939,0.0001037418,0.00004641989,0.00002704136,0.0001383044,0.00002322544,0.001618905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007646361,"threshold_uncertainty_score":0.002405465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004460748623805783,"score_gpt":0.2105345617158358,"score_spread":0.20607381309203,"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."}}