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Record W2891035494 · doi:10.1088/1361-6560/aadf7b

Understanding radionuclide production in gas target systems: the effect of adsorption on the target body

2018· article· en· W2891035494 on OpenAlex
Nicholas A. Zacchia, K. Buckley, Gregory M. Martinez, T.J. Ruth, D. Mark Martinez, Cornelia Hoehr

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysics in Medicine and Biology · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of British ColumbiaTRIUMF
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsRadionuclideNuclideAdsorptionProduction (economics)Biological systemEnvironmental scienceTerm (time)Phenomenological modelNuclear physicsComputer scienceChemistryMathematicsPhysicsStatisticsPhysical chemistry

Abstract

fetched live from OpenAlex

Gas target systems have been used for decades on cyclotrons to produce radionuclides for medical imaging. However, the activity recovered from such targets is often lower than its theoretically predicted value. Past research has suggested that nuclide interactions with the walls of the target body may play a key role in the loss of recoverable radionuclide activity. Here, we consider gas targets and modify the standard radionuclide production equation by adding a loss term representing radionuclides depositing on the walls of the target. We derive the form of the deposition term based on a simple adsorption model which is then linearized by solving for leading order terms. The resulting production equation uses one fitting parameter to give an estimate of the recoverable activity produced in a target system, taking adsorption into account. The model is then fit to six data series, taken in-house and reported in the literature and a parity plot compares model predictions to experimental data. The model is able to better track the data than any previous models, and points towards a phenomenological understanding of adsorption in target systems.

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.195

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 communication0.0000.000
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 head0.138
GPT teacher head0.344
Teacher spread0.206 · 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