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Record W2958778611 · doi:10.1088/1361-6498/ab3237

Dosimetry of a portable <i>in vivo</i> x-ray fluorescence system using EBT3 radiochromic film

2019· article· en· W2958778611 on OpenAlexafffund
James L Gräfe, Caryl Santos, Ana Pejović‐Milić

Bibliographic record

VenueJournal of Radiological Protection · 2019
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaAshland
KeywordsImaging phantomDosimetryStrontiumMaterials scienceNuclear medicineIn vivoIrradiationBiomedical engineeringDose profileRadiochemistryChemistryPhysicsMedicine

Abstract

fetched live from OpenAlex

Abstract Purpose. In vivo x-ray fluorescence is a non-invasive analytical technique for determining trace and toxic element exposures. In this work we measure the dose for a portable handheld x-ray system (pXRF). Materials and Methods . We used EBT3 radiochromic film calibrated with a clinical orthovoltage unit for absolute dose measurement. Films were placed on a human phantom and irradiated with the Tracer III-SD pXRF at tube potentials of 40 and 45 kVp with various levels of filtration. Results. Using settings that result in the best detection limits, the highest absorbed point dose to the skin was 0.3 Gy, the equivalent dose to a 1 cm 2 area was 54 mSv, and the whole-body effective dose was less than 1 μ Sv for a standard 3-min in vivo measurement of strontium or lead. Recent work has demonstrated that 1 s and 30 s measurements are feasible for bone strontium measurements, which would lead to significantly lower doses. Conclusions . Our results are in agreement with a previous dosimetry study of another portable x-ray device and indicate that it is safe for in vivo measurements of elements such as strontium and lead, only after appropriate dose validation and with appropriate beam filtration in place.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.253
Teacher spread0.235 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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