{"id":"W4296831502","doi":"10.3390/s22197145","title":"Coaxial Mach–Zehnder Digital Strain Sensor Made from a Tapered Depressed Cladding Fiber","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Financiadora de Estudos e Projetos; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Fundo para o Desenvolvimento Tecnológico das Telecomunicações; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Materials science; Optical fiber; Optics; Extinction ratio; Cladding (metalworking); Free spectral range; Mach–Zehnder interferometer; Interferometry; Fiber optic sensor; Insertion loss; Coaxial; Optoelectronics; Electrical engineering; Physics; Wavelength; Engineering; Composite material","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006620646,0.000400568,0.0003758162,0.000148333,0.0002146287,0.0001041076,0.0002894977,0.0001229619,0.002640843],"category_scores_gemma":[0.00009599054,0.0004691264,0.0001685058,0.0003086751,0.00007690668,0.0001930125,0.0001473459,0.0006635036,0.000332659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002604496,"about_ca_system_score_gemma":0.00002059775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003102372,"about_ca_topic_score_gemma":0.000002891876,"domain_scores_codex":[0.9977994,0.00006448183,0.0004143964,0.0005241204,0.000509483,0.0006881094],"domain_scores_gemma":[0.9988213,0.0003523604,0.00006693355,0.0005347827,0.00002863504,0.0001960072],"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":[0.00009452316,0.00005028086,0.0004740635,0.00002359007,0.0002559065,0.0003370715,0.001934529,0.939568,0.04783588,0.00005774876,0.001707804,0.007660631],"study_design_scores_gemma":[0.008778416,0.0003058091,0.01207119,0.00009107823,0.0003309218,0.0006091056,0.02179444,0.6405835,0.03375556,0.002812456,0.2733026,0.00556495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855575,0.000123517,0.0003794053,0.00009826993,0.0006992192,0.0003345785,0.002142103,0.001021928,0.009643457],"genre_scores_gemma":[0.9918805,0.0000058754,0.003669735,0.0001019211,0.0003176219,0.00004283584,0.0003423131,0.0002091531,0.00342999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2989845,"threshold_uncertainty_score":0.9997761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072793033585777,"score_gpt":0.2069145014813149,"score_spread":0.1961865711454571,"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."}}