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Record W2020322945 · doi:10.1016/j.egypro.2011.06.008

Research and Technology Breakthroughs in Nuclear Power for Shaping a Sustainable Low-Carbon Energy Future

2011· article· en· W2020322945 on OpenAlex
Frank Carré

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.

Bibliographic record

VenueEnergy Procedia · 2011
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsNuclear powerEngineeringSystems engineeringRisk analysis (engineering)Business

Abstract

fetched live from OpenAlex

Research for nuclear energy features high costs and long lead times as it makes use of materials testing reactors and hot laboratories, and is submitted to stringent safety regulations. These specific requirements have much contributed to make nuclear reactors evolving in an evolutionary manner. This is evidenced by currently commercialized generation III light water reactors (LWRs) that mainly rely on today's operating reactors’ technologies engineered in such a way as to optimizing their safety and economic performance. Globalization of research and development together with enhanced capabilities for science driven research allowed by more and more refined characterizatio n and numerical simulation techniques create conditions today for achieving real breakthroughs in technologies and processes, as well as in design and safety studies of nuclear systems.

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)0.000
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 score0.893
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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