{"id":"W4384701847","doi":"10.1063/5.0142798","title":"Femtosecond laser-induced Bragg gratings in silica-based fibers for harsh environment sensing","year":2023,"lang":"en","type":"article","venue":"APL Photonics","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Femtosecond; Fiber Bragg grating; Materials science; Laser; Optical fiber; Optics; Optoelectronics; Fiber optic sensor; PHOSFOS; Aerospace; Polarization-maintaining optical fiber; Physics; Engineering; Aerospace engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001723082,0.0002330102,0.0002492313,0.0001488652,0.00006120608,0.00002529887,0.0001192936,0.000135397,0.00003037501],"category_scores_gemma":[0.00006110113,0.0002784763,0.00008812986,0.0002880446,0.00002855736,0.00009089587,0.00002812463,0.000227829,0.0001218772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002210156,"about_ca_system_score_gemma":0.00002286455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001329448,"about_ca_topic_score_gemma":0.00005945919,"domain_scores_codex":[0.9986773,0.00001433314,0.0003089716,0.0003230353,0.0001599546,0.0005164754],"domain_scores_gemma":[0.9991513,0.0003360514,0.00004491489,0.000363895,0.00001167088,0.00009216159],"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":[0.00003901344,0.00003611654,0.0001196599,0.0002027988,0.00005703398,0.00007748685,0.001245761,0.6659034,0.316321,0.00008065373,0.001386468,0.01453058],"study_design_scores_gemma":[0.0009528468,0.00004659656,0.0001855699,0.00004057757,0.00001229163,0.000003162954,0.0002236365,0.7713913,0.2169643,0.0003896438,0.009446096,0.0003439362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974456,0.00002471147,0.0007870766,0.0001125766,0.0002475349,0.0005397545,0.00004259051,0.0004570856,0.0003430478],"genre_scores_gemma":[0.9784403,0.00002600557,0.02074432,0.0002449581,0.00003023834,0.00005610592,0.00008996186,0.0001364998,0.0002315382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1054879,"threshold_uncertainty_score":0.9999667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173333737405139,"score_gpt":0.2271806058112441,"score_spread":0.2098472320707302,"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."}}