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Record W2321416797 · doi:10.12943/anr.2013.00006

Hydrogen Co-Production From Subcritical Water-Cooled Nuclear Power Plants In Canada

2013· article· en· W2321416797 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAECL Nuclear Review · 2013
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsHydrogen productionHydrogenEnvironmental scienceNuclear engineeringElectricity generationNuclear powerProduction (economics)Thermal power stationPopulationSteam turbineProcess engineeringWaste managementEngineeringMechanical engineeringChemistryPower (physics)Nuclear physicsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Subcritical water-cooled nuclear reactors (Sub-WCR) operate in several countries including Canada providing electricity to the civilian population. The high-temperature-steam-electrolysis process (HTSEP) is a feasible and laboratory-demonstrated large-scale hydrogen-production process. The thermal and electrical integration of the HTSEP with Sub-WCR-based nuclear-power plants (NPPs) is compared for best integration point, HTSEP operating condition and hydrogen production rate based on thermal energy efficiency. Analysis on integrated thermal efficiency suggests that the Sub-WCR NPP is ideal for hydrogen co-production with a combined efficiency of 36%. HTSEP operation analysis suggests that higher product hydrogen pressure reduces hydrogen and integrated efficiencies. The best integration point for the HTSEP with Sub-WCR NPP is upstream of the high-pressure turbine.

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 categoriesInsufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.997

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)0.0080.004

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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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