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Nuclear Reactors

2005· other· en· W4249120187 on OpenAlexaboutno aff
Raymond L. Murray

Bibliographic record

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2005
Typeother
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear engineeringBreeder reactorNuclear powerNuclear reactorBreeder (animal)Environmental scienceNeutron fluxBoilingWaste managementProcess engineeringEngineeringNeutronMaterials scienceBlanketChemistryNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Abstract Nuclear reactors may be classified by purpose or use, key components, method of heat extraction, power level or neutron flux, or arrangement of component materials. Commercial reactors are also classified by the companies involved in design and building of the facility. Reactors used for power generation, either heat or electrical, propulsion, whether naval vessels or spacecraft, radioisotope production, materials testing, basic research, and training are discussed. The development of nuclear reactors is presented, including information gleaned from the two principal nuclear accidents of the 1980s. The pressurized lightwater reactor is the most common power generation reactor in the United States, but the boiling water reactor is also used. In Canada, heavy‐water reactors are usually employed. These and other reactors, such as the molten salt and the fast breeder reactor, are described.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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