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Record W2004852440 · doi:10.1364/ome.4.001244

ESR study of samarium doped fluorophosphate glasses for high-dose, high-resolution dosimetry

2014· article· en· W2004852440 on OpenAlexafffund
Shahrzad Vahedi, Go Okada, Cyril Koughia, Ramaswami Sammynaiken, Andy Edgar, Safa Kasap

Bibliographic record

VenueOptical Materials Express · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMinistry of Business, Innovation and Employment
KeywordsMaterials scienceDosimetrySamariumDopingHigh resolutionOpticsOptoelectronicsNuclear medicineMedicineNuclear physicsRemote sensing

Abstract

fetched live from OpenAlex

We have studied the effect of samarium doping concentration and thermal annealing on X-ray induced defect centers, including phosphorus-oxygen hole and electron centers (POHC and POEC), in Sm3+-doped fluorophosphate glasses towards developing a potential high-dose, high-resolution detector for microbeam radiation therapy. ESR measurements show that defect center formation is suppressed by increasing the Sm-dopant concentration with POECs more strongly influenced than POHCs. This can be explained by a model based on the competition between defect center formations and Sm3+ ⇆ Sm2+ interconversion. Thermal annealing at increasing moderate temperatures (TA = 100−300 °C) reduces the POHC related ESR and induced absorbance bands while those of POEC continue to survive. ESR measurements over a wider range show the trace of a very broad ESR signal in samples containing Sm2+ ions including those annealed at temperatures between 350 °C and glass transition temperature (Tg ≈ 460 °C). Finally, thermal annealing at 550 °C (> Tg) totally erases all the ESR signals and restores the sample to its original unirradiated state.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations25
Published2014
Admission routes2
Has abstractyes

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