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Record W2047603100 · doi:10.1115/icone10-22644

Next Generation CANDU Core Physics Innovations

2002· article· en· W2047603100 on OpenAlexaff
P. S. W. Chan, J. M. Hopwood, J. W. Love

Bibliographic record

Venue10th International Conference on Nuclear Engineering, Volume 2 · 2002
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsBurnupNuclear engineeringCoolantNatural uraniumUraniumThorium fuel cycleNatural circulationEnriched uraniumNuclear physicsMaterials scienceMOX fuelPhysicsEngineering

Abstract

fetched live from OpenAlex

NG CANDU is the “Next Generation” CANDU® reactor, aimed at producing electrical power at a capital cost significantly less than that of the current reactor designs. A key element of cost reduction is the use of H2O as coolant and Slightly Enriched Uranium fuel in a tight D2O-moderated lattice. The innovations in the CANDU core physics result in substantial improvements in economics as well as significant enhancements in reactor licensability, controllability, and waste reduction. The full-core coolant-void reactivity in NG CANDU is about −3 mk. Power coefficient is substantially negative. Fuel burnup is about three times the current natural-uranium burnup.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score1.000

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)0.0030.001

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 head0.088
GPT teacher head0.230
Teacher spread0.142 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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