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Record W2961723884 · doi:10.15392/bjrs.v7i3a.880

Monitoring internal contamination from OEW of an 18F-FDG production plant: WBC or head counting setup?

2019· article· en· W2961723884 on OpenAlexaff
Bruno Melo Mendes, Bruno Machado Trindade, Telma Cristina Ferreira Fonseca, Tarcísio Passos Ribeiro de Campos

Bibliographic record

VenueBrazilian Journal of Radiation Sciences · 2019
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of Ottawa
FundersComissão Nacional de Energia NuclearFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsBiodistributionCalibrationNuclear medicineInternal dosimetryPositron emission tomographyGamma cameraHead (geology)Biomedical engineeringComputer scienceMaterials scienceNuclear engineeringIn vivoDosimetryMedicineMathematicsEngineeringStatistics

Abstract

fetched live from OpenAlex

The production 18F-FDG for positron emission tomography (PET) has consistently increased over the past two decades. The risk of internal contamination at 18F-FDG production facilities exists. A setup for evaluation of the 18F-FDG activity incorporated into the OEW brain, called Head Counting System (HCS), was presented in previous works. In this study, the whole body counter setup (WBC) was evaluated for monitoring 18F incorporations. The Monte Carlo Virtual Software (VMC in-vivo) and the MCNPx code were used to assess the system calibration coefficient (CC). Three 18F distributions were simulated: i) uniformly distributed in soft tissue (UDST); ii) Na18F biodistribution (NAFB); and iii) 18F-FDG biodistribution (FDGB). The calibration coefficient of WBC was compared to the current head counting system CC under the same biodistribution conditions. The ICRP male reference voxelized phantoms (RCP_AM) was used in the simulations. The results showed that the WBC setup was more efficient than the head counter for all the studied 18F distributions: UDST = 1060 %, FDGB = 488 % and NAFB = 340 %. Despite this, especially for 18F-FDG, the possibility of bladder voiding before measurement can lead to considerable uncertainties when the WBC setup is used. On the other hand, bladder activity does not show great influence the calibration coefficient of the head counting system. Future work will evaluate the WBC sources of uncertainties in the measurement of 18F incorporated activity.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.037
GPT teacher head0.363
Teacher spread0.326 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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