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Record W2068334233 · doi:10.1063/1.4797459

An alternate approach to the production of radioisotopes for nuclear medicine applications

2013· article· en· W2068334233 on OpenAlexafffund
J.M. D’Auria, R. Keller, Keith Ladouceur, Suzanne E. Lapi, Thomas J. Ruth, P. W. Schmor

Bibliographic record

VenueReview of Scientific Instruments · 2013
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsTRIUMFBC Cancer AgencySimon Fraser University
FundersTRIUMF
KeywordsIsotopeRadiochemistryNatural abundanceRadionuclideNuclear engineeringIsotope separationImpurityNuclear physicsNuclear reactionMaterials sciencePhysicsChemistryEngineering

Abstract

fetched live from OpenAlex

There is a growing need for the production of radioisotopes for both diagnostic and therapeutic medical applications. Radioisotopes that are produced using the (n,γ) or (γ,n) reactions, however, typically result in samples with low specific activity (radioactivity∕gram) due to the high abundance of target material of the same element. One method to effectively remove the isotopic impurity is electro-magnetic mass separation. An Ion Source Test Facility has been constructed at TRIUMF to develop high-intensity, high-efficiency, reliable ion sources for purification of radioactive isotopes, particularly those used in nuclear medicine. In progress studies are presented.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.199

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 head0.042
GPT teacher head0.345
Teacher spread0.302 · 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 designNot applicable
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

Citations6
Published2013
Admission routes2
Has abstractyes

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