{"id":"W2060537416","doi":"10.3390/s130201836","title":"Distributed Temperature and Strain Discrimination with Stimulated Brillouin Scattering and Rayleigh Backscatter in an Optical Fiber","year":2013,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"Distributed acoustic sensing; Reflectometry; Backscatter (email); Rayleigh scattering; Brillouin scattering; Brillouin zone; Materials science; Optics; Optical time-domain reflectometer; Optical fiber; Fiber optic sensor; Temperature measurement; Dispersion (optics); Image resolution; Strain (injury); Time domain; Polarization-maintaining optical fiber; Physics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004554771,0.0002272902,0.0002060379,0.00009324178,0.00003787105,0.00009777478,0.00004887064,0.0001254434,0.00006570535],"category_scores_gemma":[0.0000157052,0.0001970393,0.00001210374,0.0001604354,0.0001092326,0.0003334419,0.00002111761,0.0002337824,0.00001717525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004682279,"about_ca_system_score_gemma":0.000003592194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000222466,"about_ca_topic_score_gemma":0.00005151124,"domain_scores_codex":[0.9990653,0.00002479444,0.0001912103,0.0002897622,0.0001163033,0.0003125682],"domain_scores_gemma":[0.999558,0.00005996655,0.00001853712,0.0001819602,0.00003922823,0.0001423139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00009773603,0.00009522508,0.02727089,0.0003440006,0.0001129352,0.000155369,0.00410541,0.5838468,0.3602728,0.0001486269,0.0002094478,0.02334078],"study_design_scores_gemma":[0.001766085,0.0001495361,0.7861116,0.0001945855,0.00003696099,0.0001511996,0.001080081,0.2017856,0.007641778,0.0001462601,0.0001073777,0.0008289269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989732,0.00003229592,0.0001097302,0.0002518541,0.0000311305,0.0003002245,0.00003236425,0.000143871,0.0001253561],"genre_scores_gemma":[0.9952551,0.000009051241,0.004439916,0.0000342162,0.00003097183,0.00001188242,0.00008605484,0.00005262954,0.0000801599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7588407,"threshold_uncertainty_score":0.8035031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006398597354748219,"score_gpt":0.2092625241951757,"score_spread":0.2028639268404275,"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."}}