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Record W1965903241 · doi:10.1115/1.4029420

Nuclear Power as a Basis for Future Electricity Generation

2014· article· en· W1965903241 on OpenAlex

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

VenueJournal of Nuclear Engineering and Radiation Science · 2014
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsNuclear powerElectricity generationGeothermal energyEnergy developmentEnvironmental scienceEnergy independenceWind powerFossil fuelRenewable energyCoalEnergy sourceElectric powerElectricityThermal power stationGeothermal gradientWaste managementPower (physics)EngineeringElectrical engineeringGeologyPhysics

Abstract

fetched live from OpenAlex

It is well known that electrical power generation is the key factor for advances in industry, agriculture, technology, and standards of living. Also, a strong power industry with diverse energy sources is very important for a nation’s independence. In general, electrical energy can be generated from (1) burning mined and refined energy sources such as coal, natural gas, oil, and nuclear; and (2) harnessing energy sources such as hydro, biomass, wind, geothermal, solar, and wave power. Today, the main sources for electrical energy generation are (1) thermal power, primarily using coal and secondarily natural gas; (2) “large” hydraulic power from dams and rivers; and (3) nuclear power from various reactor designs. The balance of the energy sources is from using oil, biomass, wind, geothermal, and solar, which have a visible impact just in some countries. This paper presents the current status and role of the nuclear-power industry in the world with a comparison of nuclear-energy systems to other energy 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.258

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)0.0000.000

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 head0.005
GPT teacher head0.209
Teacher spread0.203 · 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