{"id":"W2095181835","doi":"10.1364/oe.14.003152","title":"Optimization of a continuous phase-only sampling for high channel–count fiber Bragg gratings","year":2006,"lang":"en","type":"article","venue":"Optics Express","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Optics; Materials science; Channel spacing; Fiber Bragg grating; Channel (broadcasting); Phase (matter); Fabrication; Diffraction; Optoelectronics; Wavelength-division multiplexing; Optical fiber; Telecommunications; Computer science; Physics","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":[0.0003370297,0.000495505,0.0003085998,0.0002406596,0.0002053777,0.0003862721,0.0004305915,0.000250896,0.0003753434],"category_scores_gemma":[0.0005306266,0.000232487,0.0001537136,0.0002648752,0.000260025,0.0002932671,0.0001728401,0.0001886355,0.0001165803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000727298,"about_ca_system_score_gemma":0.0006868712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001088921,"about_ca_topic_score_gemma":0.001998962,"domain_scores_codex":[0.9998013,0.00002443193,0.0000107263,0.00004118755,0.00009228836,0.00003009331],"domain_scores_gemma":[0.9996885,0.0001107178,0.00007564395,0.00003113372,0.00006654947,0.00002749575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003095788,0.0001664844,0.001396395,0.00008210706,0.00001911408,0.00006065546,0.00004649648,0.03536597,0.9374446,0.002004382,0.0002516392,0.02285263],"study_design_scores_gemma":[0.00009382555,0.000346762,0.002748965,0.000004325514,0.00001889438,0.0001088724,0.0000127605,0.394382,0.600573,0.0002777119,0.001409087,0.00002371854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8299485,0.0003142247,0.1675281,0.00007387917,0.00003310891,0.00005218762,0.00006691361,0.0004392591,0.001543792],"genre_scores_gemma":[0.894638,0.00008763263,0.1046518,0.00001358892,0.00001648958,0.00003809793,0.00006565596,0.00004443764,0.0004443137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001088921,"threshold_uncertainty_score":0.005276918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168216916084583,"score_gpt":0.2410139545112788,"score_spread":0.2293317853504329,"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."}}