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Characterization and mapping of the neutron fields around Bruce Power’s 177Lu isotope production system

2024· article· en· W4392640355 on OpenAlexaffabout
Andrei Hanu, J. Atanackovic, Craige Boyd, Eric M. Johnston, A.J. Waker

Bibliographic record

VenueApplied Radiation and Isotopes · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of Ontario Institute of TechnologyOntario Power GenerationBruce Power (Canada)McMaster University
Fundersnot available
KeywordsNeutronNuclear engineeringNuclear physicsNeutron temperatureEquivalent doseEnvironmental scienceResearch reactorPhysicsRadiochemistryChemistryEngineering

Abstract

fetched live from OpenAlex

Bruce Power operates a first-of-its-kind isotope production system (IPS) that enables continuous production of 177Lu within Canada Deuterium Uranium (CANDU) commercial power reactors. Located on the reactivity mechanisms deck of Unit 7, just outside of reactor containment but in close proximity to the primary heat transport (PHT) pumps, this facility offers unique advantages for 177Lu production. However, employees working in this area encounter a radiation hazard which consists primarily of photoneutrons. These originate from the base of the PHT pumps and are only present when the reactor is operating. This study evaluates neutron exposure at Bruce Power’s IPS by using a nested neutron spectrometer (NNS) to determine the neutron energy spectra and absolute dosimetric quantities such as the ambient dose equivalent, H*(10). The results from the NNS are then compared to surveys performed by a portable neutron rem meter (Model NP-2 by Nuclear Research Corporation), routinely used by Bruce Power staff for workplace monitoring. While the Model NP-2 generally showed consistent results across locations, a 50% dose correction factor was identified when operators were harvesting 177Lu from the IPS. This finding highlights an opportunity to reduce the neutron dose that is assigned to operators when producing 177Lu.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.256

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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