{"id":"W4386593678","doi":"10.3390/photonics10080864","title":"Investigation of Hybrid Remote Fiber Optic Sensing Solutions for Railway Applications","year":2023,"lang":"en","type":"article","venue":"Photonics","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Optiwave Systems (Canada)","funders":"","keywords":"Fiber Bragg grating; Computer science; Optical fiber; Fiber optic sensor; SIGNAL (programming language); Wavelength; Photodetector; Electronic engineering; Optics; Telecommunications; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001334075,0.00009711381,0.0001275514,0.0001005706,0.00008621148,0.000008193651,0.00007046216,0.00003508553,0.000008097638],"category_scores_gemma":[0.00005672187,0.0001173709,0.00005633695,0.0003544554,0.00004852065,0.00006408319,0.00002356818,0.00008285196,0.00008999486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006611428,"about_ca_system_score_gemma":0.00002273169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003053465,"about_ca_topic_score_gemma":0.000002585092,"domain_scores_codex":[0.9992877,0.00000661555,0.0002155502,0.0001367808,0.00009017353,0.0002632411],"domain_scores_gemma":[0.9993734,0.0001860785,0.00004115111,0.0002720026,0.00007339494,0.00005401688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005419601,0.000003993421,0.000004660312,0.000268406,0.00006928492,0.000002642042,0.000352775,0.8889564,0.0940026,0.001912851,0.00253701,0.01188399],"study_design_scores_gemma":[0.0001611868,0.000008118027,0.00002584663,0.00002390025,0.00002550446,0.00001012752,0.00003865752,0.9261201,0.05299798,0.005536121,0.01492694,0.000125514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5016592,0.0003070004,0.4905187,0.0002495681,0.0003878026,0.001728533,0.0001693338,0.001640481,0.003339419],"genre_scores_gemma":[0.3880997,0.0001691164,0.6098977,0.00006503969,0.0001046115,0.00009824776,0.0002912312,0.0001728208,0.001101518],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.119379,"threshold_uncertainty_score":0.4786245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03254754106162545,"score_gpt":0.2497137626924136,"score_spread":0.2171662216307882,"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."}}