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Record W2080118273 · doi:10.1080/08929880600993071

Feasibility of Eliminating the Use of Highly Enriched Uranium in the Production of Medical Radioisotopes

2006· article· en· W2080118273 on OpenAlexaboutno aff
Frank von Hippel, Laura H. Kahn

Bibliographic record

VenueScience and Global Security · 2006
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnriched uraniumUraniumProduction (economics)BusinessEnvironmental scienceProduction costWaste managementNuclear physicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Significant quantities of highly enriched uranium (HEU)—more than enough to make a Hiroshima bomb—are used annually as neutron target material in Canadian, European, and South African reactors to produce the short-lived fission products used in nuclear medicine. The most important of these fission products is 99Mo, which decays into 99mTc, which is the most widely used medical radioisotope. The U.S. supplies weapon-grade uranium to the Canadian radioisotope producer and might in the future provide it to the European producers as well. As a condition for receiving U.S. HEU, the 1992 Schumer Amendment to the U.S. Atomic Energy Act requires that a foreign producer cooperate with the United States in converting to low-enriched uranium (LEU) targets. Some smaller producers have already done so. The Canadian producer has asserted, however, that the cost of conversion would be too high. The 2005 Burr amendment therefore exempted radioisotope producers in Canada and Europe from the Schumer amendment's requirements but requested a National Academy of Sciences study of the feasibility of conversion, setting as a feasibility test that the production cost be increased by no more than 10 percent. We show that paying for the conversion for the largest European production facility would increase the cost of 99Mo production there by only a few percent. For the Canadian facility the production cost could be more than 10 percent but the increase in the cost of the final 99mTc-containing radiopharmaceutical would be only about 1 percent. It is also pointed out that savings in security could well dwarf the costs of converting to LEU if HEU were no longer present at the production and radioactive waste sites.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.029
GPT teacher head0.290
Teacher spread0.261 · 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 designTheoretical or conceptual
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

Citations18
Published2006
Admission routes1
Has abstractyes

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