{"id":"W4377819156","doi":"10.1016/j.jnoncrysol.2023.122398","title":"Customizing nanoparticle characteristics in Ba-rich nanoparticle-doped optical fibers to tune Rayleigh scattering","year":2023,"lang":"en","type":"article","venue":"Journal of Non-Crystalline Solids","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Canada First Research Excellence Fund; Canada Foundation for Innovation; Université Laval","keywords":"Rayleigh scattering; Nanoparticle; Materials science; Optical fiber; Scattering; Nanotechnology; Doping; Fabrication; Fiber; Light scattering; Optoelectronics; Chemical engineering; Optics; Composite material","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":[0.0007237772,0.0003320513,0.0007021657,0.0005594979,0.00006790282,0.00008471221,0.0003633549,0.0001198047,0.00004354473],"category_scores_gemma":[0.0002930567,0.0003336734,0.0001391586,0.001298596,0.00005919388,0.0004016373,0.0001250837,0.0005406651,0.0001729493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002886635,"about_ca_system_score_gemma":0.00005637265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002703745,"about_ca_topic_score_gemma":0.000006632728,"domain_scores_codex":[0.9970196,0.00004046205,0.001322326,0.0002523539,0.0004902481,0.0008749738],"domain_scores_gemma":[0.998675,0.0002331245,0.0001699379,0.0003244217,0.000164009,0.0004335465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001126025,0.00005606398,0.001677019,0.00007320004,0.00005637058,0.0005535178,0.001048838,0.2117039,0.7819121,0.00001320445,0.0004950922,0.002298063],"study_design_scores_gemma":[0.006353057,0.0008697651,0.05448341,0.001217677,0.0001837181,0.0006054259,0.001869612,0.4979824,0.4283603,0.0002352391,0.005992336,0.001846981],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935194,0.00004441238,0.004531186,0.0005998151,0.0006982802,0.0002199021,0.000007622334,0.0001693078,0.0002101036],"genre_scores_gemma":[0.9872058,0.00007329323,0.01187328,0.0001376797,0.0004476827,0.00001108806,0.000003770551,0.000119382,0.0001280261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3535518,"threshold_uncertainty_score":0.9999115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388597444001992,"score_gpt":0.2569136421321866,"score_spread":0.2430276676921667,"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."}}