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Record W2065514493 · doi:10.1118/1.4742865

The effect of different bleaching wavelengths on the sensitivity of Al<sub>2</sub>O<sub>3</sub>:C optically stimulated luminescence detectors (OSLDs) exposed to 6 MV photon beams

2012· article· en· W2065514493 on OpenAlexaff
Azeez Omotayo, Joanna Cygler, Gabriel O. Sawakuchi

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsOttawa HospitalCarleton University
Fundersnot available
KeywordsOptically stimulated luminescenceIrradiationMaterials scienceOpticsWavelengthNanodotNuclear medicineDosimetryLuminescenceOptoelectronicsPhysicsMedicineNuclear physics

Abstract

fetched live from OpenAlex

PURPOSE: To determine the effect of different bleaching wavelengths on the response of Al(2)O(3):C optically stimulated luminescence detectors (OSLDs) exposed to accumulated doses of 6 MV photon beams. METHODS: In this study the authors used nanoDot OSLDs readout with a MicroStar reader. The authors first characterized the dose-response, fading, and OSL signal loss of OSLDs exposed to doses from 0.5 to 10 Gy. To determine the effect of different bleaching wavelengths on the OSLDs' response, the authors optically treated the OSLDs with 26 W fluorescent lamps in two modes: (i) directly under the lamps for 10, 120, and 600 min and (ii) with a long-pass filter for 55, 600, and 2000 min. Changes in the OSLDs' sensitivity were determined for an irradiation-readout-bleaching-readout cycle after irradiations with 1 and 10 Gy dose fractions. RESULTS: The OSLDs presented supralinearity for doses of 2 Gy and above. The signal loss rates for sequential readouts were (0.287 ± 0.007)% per readout in the reader's strong-stimulation mode, and (0.019 ± 0.002)% and (0.035 ± 0.007)% per readout for doses of 0.2 and 10 Gy, respectively, in the reader's weak-stimulation mode. Fading half-life values ranged from (0.98 ± 0.14) min to (1.77 ± 0.24) min and fading showed dose dependence for the first 10-min interval. For 10 and 55 min bleaching using modes (i) and (ii), the OSL signal increased 14% for an accumulated dose of 7 Gy (1 Gy fractions). For OSLDs exposed to 10 Gy fractions, the OSL signal increased 30% and 25% for bleaching modes (i) and (ii) and accumulated dose of 70 Gy, respectively. For 120 and 600 min bleaching using modes (i) and (ii), the OSL signal increased 2.7% and 1.5% for an accumulated dose of 7 Gy (1 Gy fractions), respectively. For 10 Gy fractions, the signal increased 14% for bleaching mode (i) (120 min bleaching) and decreased 1.3% for bleaching mode (ii) (600 min bleaching) for an accumulated dose of 70 Gy. For 600 and 2000 min bleaching using modes (i) and (ii), the signal increased 2.3% and 1.8% for an accumulated dose of 7 Gy (1 Gy fractions), respectively. For 10 Gy fractions, the signal increased 10% for mode (i) (600 min bleaching) and decreased 2.5% for mode (ii) (2000 min bleaching) for an accumulated dose of 70 Gy. CONCLUSIONS: The dose-response of nanoDot OSLDs read using the MicroStar reader presented supralinearity for doses of 2 Gy and above. The signal loss as a function of sequential readouts depended on dose. Fading also depended on dose for the first 10-min interval. For dose fractions of 1 and 10 Gy, OSLDs may be reused within 3% and 5% accuracies up to the maximum accumulated dose of 7 and 70 Gy investigated in this study, respectively. These accuracies were obtained after the OSLDs were bleached with a light source with wavelengths above about 495 nm. The authors also concluded that changes in sensitivity of OSLDs depended on bleaching time, accumulated dose, and wavelength spectrum of the bleaching source.

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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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
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 head0.010
GPT teacher head0.238
Teacher spread0.227 · 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".

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Citations36
Published2012
Admission routes1
Has abstractyes

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