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Record W4409058117 · doi:10.1109/tns.2025.3553065

Pre-Irradiation Influence on Proton Radioluminescence Responses of Sol-Gel Optical Fibers

2025· article· en· W4409058117 on OpenAlexafffund
Fiammetta Fricano, Adriana Morana, Cornelia Hoehr, Cosimo Campanella, C. Bélanger-Champagne, M. Trinczek, Damien Lambert, Philippe Paillet, Hicham El Hamzaoui, Bruno Capoen, Mohamed Bouazaoui, A. Boukenter, Emmanuel Marin, Y. Ouerdane, Sylvain Girard

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsTRIUMF
FundersEuropean Regional Development FundNational Research Council CanadaAgence Nationale de la Recherche
KeywordsRadioluminescenceIrradiationProtonMaterials scienceOptical fiberOptoelectronicsRadiochemistryOpticsNuclear physicsPhysicsDetectorChemistry

Abstract

fetched live from OpenAlex

We measured the radiation induced luminescence (RIL) of sol-gel made silica-based optical fibers under protons with energy varying between ~27 and 63 MeV. We compared simultaneously the responses of a pristine (i.e., not irradiated) sample and one pre-irradiated under X-rays up to 250 kGy of the different fiber types (cerium, copper, and cerium/terbium co-doped fibers). The obtained results highlight better performances for pre-irradiated samples, thanks to the progressive deep trap filling and reduction of the bright burn effect (BBE). The dose deposited by the protons and the dose rate range within the fiber-sensitive volumes are obtained through Monte Carlo simulations. We observed good linearity of the RIL versus the dose rate in the 1.5–12-Gy(SiO2)/s range and for the different tested proton energies. In particular, no energy dependence is noticed regarding the RIL, within a 5% maximum. All of these characteristics are especially important for proton therapy, where the linear energy transfer changes along the Bragg peak during the tumor treatment. Sol-gel silica-based optical fibers constitute promising solutions for proton flux (or dose rate) monitoring during treatments, providing high spatial resolution.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.262
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

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