{"id":"W2055791006","doi":"10.1063/1.3405839","title":"High performance resonance Raman spectroscopy using volume Bragg gratings as tunable light filters","year":2010,"lang":"en","type":"article","venue":"Review of Scientific Instruments","topic":"Mechanical and Optical Resonators","field":"Physics and Astronomy","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Photon Etc (Canada); Université de Montréal; Regroupement Québécois sur les Matériaux de Pointe","funders":"National Research Council Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Raman spectroscopy; Materials science; Monochromator; Grating; Optics; Fiber Bragg grating; Optoelectronics; Laser; Coherent anti-Stokes Raman spectroscopy; Resonance (particle physics); Wavelength; Raman scattering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006375679,0.0004953277,0.0004424673,0.0004908855,0.0001587488,0.0005093602,0.0007232763,0.0005484823,0.0002768037],"category_scores_gemma":[0.0003300394,0.000304794,0.0003656445,0.0003671905,0.000423452,0.0005269985,0.0003753167,0.0003962568,0.0003428215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004899898,"about_ca_system_score_gemma":0.0002130366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000535582,"about_ca_topic_score_gemma":0.0009439047,"domain_scores_codex":[0.9991986,0.0001154591,0.00004431393,0.0002010264,0.0003633511,0.00007726982],"domain_scores_gemma":[0.9997544,0.00006825421,0.00004367702,0.00003620196,0.0000765392,0.00002102088],"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":[0.00001529633,0.00000749949,0.0001266628,0.00003073724,0.000005182345,0.00001817566,0.00001191402,0.0003614145,0.9936222,0.0004799386,0.00003343111,0.005287495],"study_design_scores_gemma":[0.000005373948,0.00007712128,0.0002993621,0.000003316573,0.000008924108,0.00007108364,0.000009011306,0.004261902,0.9934343,0.000172567,0.001646033,0.00001108416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6631986,0.00624036,0.323661,0.0002456824,0.0002168749,0.0001492309,0.0002468635,0.001380861,0.004660485],"genre_scores_gemma":[0.712621,0.001743864,0.2824997,0.00009254527,0.00005313688,0.00006923578,0.0001903409,0.00007371502,0.002656522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007232763,"threshold_uncertainty_score":0.003555179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008965821713615865,"score_gpt":0.2524286704409121,"score_spread":0.2434628487272962,"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."}}