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Record W2609113519 · doi:10.12943/cnr.2016.00030

VALIDATIONS OF GAMMA MEASUREMENTS IN RESEARCH REACTORS WITH MCNP FULL-REACTOR MODELS

2017· article· en· W2609113519 on OpenAlex
Thai Sinh Nguyen, Xiaolin Wang, Shuwei Yue

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCNL Nuclear Review · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsNuclear engineeringPhotonCriticalityResearch reactorNeutronNuclear physicsGamma rayIntensity (physics)PhysicsEnvironmental scienceMaterials scienceRadiochemistryChemistryOpticsEngineering

Abstract

fetched live from OpenAlex

MCNP full-reactor models of the SLOWPOKE-2 and ZED-2 research reactors have been used for calculating gamma spectra and dose rates at locations where measurements were made. In addition to neutrons, MCNP criticality calculations are capable of tracking reactor prompt photons in space and energy, which can be tallied at locations of interest. Delayed photons from conceivable sources can be approximately included in the calculations, contributing to as much as one-third of the local photon intensity or committed dose rate in this study. Discrepancies between the MCNP calculated and measured results are analyzed for causes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.413

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 head0.348
GPT teacher head0.427
Teacher spread0.079 · 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