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Record W2167200085 · doi:10.1118/1.1951447

Characterization and real‐time optical measurements of the ionizing radiation dose response for a new radiochromic medium

2005· article· en· W2167200085 on OpenAlexaff
Alexandra Rink, I. Alex Vitkin, David A. Jaffray

Bibliographic record

VenueMedical Physics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
FundersNational Institute on AgingNational Institutes of Health
KeywordsDosimeterDosimetryIonizing radiationMaterials scienceRadiationOpticsAbsorbanceAbsorbed doseOptical densityDose rateWavelengthIrradiationNuclear medicineOptoelectronicsPhysicsMedical physicsNuclear physicsMedicine

Abstract

fetched live from OpenAlex

A new radiochromic film, GafChromic EBT, was investigated for use in a real-time radiation dosimetry system. It was found to be approximately eight times more sensitive to ionizing radiation dose, exhibited less postexposure development and achieved stable readout faster than one of its predecessors, GafChromic MD-55. A clear distinction in change in optical density between exposure and postexposure was observed, but the measurements obtained during exposure were not linear with time or dose. This could not be explained by a shift in wavelength of maximum change in absorbance, as it was stable at approximately 636 nm during the entire exposure range (up to 9.52 Gy). Increasing the spectral window of interest over which calculations were performed did little to correct the nonlinearity. The radiochromic film exhibited small dose rate dependence in real-time measurements, with an increase in standard deviation of change in optical density measurements from 0.9% to 1.8% over a sixfold variation in dose rate. Overall, GafChromic EBT has increased sensitivity and decreased postexposure darkening, and this bodes well for its potential role as a radiation dosimeter, including real-time applications.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.581
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.284
Teacher spread0.267 · 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

Citations80
Published2005
Admission routes1
Has abstractyes

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