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Record W2515446428 · doi:10.1088/2058-7058/20/7/31

Driving the hydrogen economy

2007· article· en· W2515446428 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

VenuePhysics World · 2007
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHydrogen economyFossil fuelCombustionCoalHydrogen fuelHydrogenEnvironmental scienceElectricityHydrogen fuel enhancementChemical energyWaste managementInternal combustion engineElectricity generationProcess engineeringPower (physics)EngineeringChemistryAutomotive engineeringThermodynamics

Abstract

fetched live from OpenAlex

A global "hydrogen economy", in which energy is provided by hydrogen instead of fossil fuels, has long been dreamed of as a way of ending our dependence on coal and oil. In such a world, fuel cells would replace the internal combustion engines in cars and the steam turbines in power stations as the means of turning chemical energy into useful power. Rather than burning carbon-based fuels and therefore releasing carbon dioxide, fuel cells convert the chemical energy of hydrogen directly into electricity, producing only water as a by-product. Furthermore, since a fuel cell is not subject to the same thermodynamic constraints as a heat engine it can be made much more efficient than an internal combustion engine.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.607

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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