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Record W2037683728 · doi:10.1093/rpd/ncr389

MCNPX alpha particle dose estimate to the skin tissue from a low-enriched uranium fuel fragment

2011· article· en· W2037683728 on OpenAlexaff
J. Atanackovic

Bibliographic record

VenueRadiation Protection Dosimetry · 2011
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsAtomic Energy (Canada)Canadian Nuclear Laboratories
Fundersnot available
KeywordsUraniumDosimetryFragment (logic)Alpha particleEnriched uraniumEnvironmental scienceNuclear medicineRadiochemistryMedical physicsNuclear engineeringMedicineEngineeringNuclear physicsPhysicsChemistryComputer science

Abstract

fetched live from OpenAlex

Three alpha volume sources (low-enriched uranium-U(3)Si) were analysed using Monte Carlo modelling in order to calculate the dose delivered to the dermis from a small embedded fuel fragment (sliver). Three shapes were analysed using MCNPX 2.6.0 code: sphere, cylinder and parallelepiped. Essentially, two kinds of runs were performed: count rate run and dosimetry run. The two results were combined to estimate dose coefficients that can be used for alpha dose assessments in the field. The two results were obtained for the 1 and 0 cm counting geometries. These results are very stable and show that the actual dose delivered to the skin per unit count rate for the recovered particle is independent of the shape of the volume alpha source.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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 designSimulation or modeling
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
Published2011
Admission routes1
Has abstractyes

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