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Validating production of PET radionuclides in solid and liquid targets: Comparing Geant4 predictions with FLUKA and measurements

2017· article· en· W2779069225 on OpenAlexafffund
T. Amin, Angelo Infantino, R. J. Barlow, Cornelia Hoehr

Bibliographic record

VenueApplied Radiation and Isotopes · 2017
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsTRIUMF
FundersTRIUMF
KeywordsMonte Carlo methodCyclotronRadionuclideProtonPhysicsProton therapyNuclear physicsIsotopeRadiochemistryMaterials scienceNuclear medicineChemistryMedicineMathematicsStatisticsElectron

Abstract

fetched live from OpenAlex

Tc, which have been produced using a 13MeV medical cyclotron. The results are compared to previous simulations with the Monte Carlo code FLUKA and experimental measurements. The comparison shows variable degrees of agreement for different isotopes. The mean absolute deviation of Monte Carlo results from experiments was 1.4±1.6 for FLUKA and 0.7±0.5 for Geant4 using TENDL cross sections with QGSP-BIC-AllHP physics. Both agree well within the large error, which is due to the uncertainties present in both experimentally determined and theoretical reaction cross sections. Overall, Geant4 has been confirmed as a tool to simulate radionuclide production at low proton energy.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.340

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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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

Citations11
Published2017
Admission routes2
Has abstractyes

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