{"id":"W2158861463","doi":"10.1109/jlt.2011.2123081","title":"Real-Time Interrogation of a Linearly Chirped Fiber Bragg Grating Sensor Based on Chirped Pulse Compression With Improved Resolution and Signal-to-Noise Ratio","year":2011,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Fiber Bragg grating; Optics; Waveform; Interferometry; Pulse compression; Chirp; Materials science; Free spectral range; Fiber optic sensor; SIGNAL (programming language); Spectral resolution; Noise (video); Physics; Wavelength; Optical fiber; Laser; Spectral line; 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":[0.0004097903,0.0003489955,0.00027878,0.0002458563,0.0001188452,0.0002800804,0.0004870925,0.0004933738,0.0003017293],"category_scores_gemma":[0.0008882848,0.0001981215,0.0001107076,0.0002393642,0.0004151365,0.0005879239,0.0002360791,0.0003074358,0.0001137707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003081665,"about_ca_system_score_gemma":0.0002554259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000450184,"about_ca_topic_score_gemma":0.0007737936,"domain_scores_codex":[0.9996499,0.0000714228,0.0000137432,0.00006425493,0.0001803171,0.00002046214],"domain_scores_gemma":[0.9995183,0.0002022088,0.0001218914,0.00003760309,0.00009444152,0.00002552542],"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":[0.00008481165,0.00002380255,0.0003181946,0.00003868361,0.000004515153,0.00005165806,0.00003537897,0.0006202572,0.9851329,0.0002046131,0.00005102809,0.01343419],"study_design_scores_gemma":[0.00001608682,0.0002042056,0.001157137,0.000004279426,0.00001077501,0.0002774555,0.00001939296,0.03708342,0.9606913,0.00009973405,0.0004192778,0.00001705637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8219289,0.001006929,0.1743782,0.0002782377,0.00009519948,0.00007165722,0.00005572788,0.0006560319,0.001529096],"genre_scores_gemma":[0.8490299,0.0002833178,0.1496469,0.0001113067,0.00002806344,0.00003592893,0.00003690893,0.00001680882,0.0008109433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004933738,"threshold_uncertainty_score":0.002235949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009179473799475962,"score_gpt":0.211517778408941,"score_spread":0.2023383046094651,"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."}}