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Record W2117198812 · doi:10.1118/1.2841940

Radiotherapy dosimetry using a commercial OSL system

2008· article· en· W2117198812 on OpenAlexaff
A. Viamonte, L.A.R. da Rosa, Lesley Buckley, Amanda Cherpak, Joanna Cygler

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsCarleton UniversityOttawa Regional Cancer FoundationOttawa Hospital
FundersInternational Atomic Energy Agency
KeywordsOptically stimulated luminescenceDosimetryDosimeterIonization chamberMaterials scienceRadiationDose profileOpticsRadiation therapyDetectorParticle detectorNuclear medicineIonizationPhysicsMedicineRadiology

Abstract

fetched live from OpenAlex

A commercial optically stimulated luminescence (OSL) system developed for radiation protection dosimetry by Landauer, Inc., the InLight microStar reader, was tested for dosimetry procedures in radiotherapy. The system uses carbon-doped aluminum oxide, Al2O3:C, as a radiation detector material. Using this OSL system, a percent depth dose curve for 60Co gamma radiation was measured in solid water. Field size and SSD dependences of the detector response were also evaluated. The dose response relationship was investigated between 25 and 400 cGy. The decay of the response with time following irradiation and the energy dependence of the Al2O3:C OSL detectors were also measured. The results obtained using OSL dosimeters show good agreement with ionization chamber and diode measurements carried out under the same conditions. Reproducibility studies show that the response of the OSL system to repeated exposures is 2.5% (1sd), indicating a real possibility of applying the Landauer OSL commercial system for radiotherapy dosimetric procedures.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.006

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 head0.025
GPT teacher head0.270
Teacher spread0.245 · 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

Citations148
Published2008
Admission routes1
Has abstractyes

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