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Record W2566100505 · doi:10.2172/1170355

Hydrogen Energy Storage: Grid and Transportation Services (Technical Report)

2015· report· en· W2566100505 on OpenAlexaboutno aff
Marc Melaina, Joshua Eichman

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyEnvironmental economicsSmart gridGreenhouse gasGridBusinessEngineeringEnvironmental scienceComputer scienceElectrical engineeringEconomics

Abstract

fetched live from OpenAlex

Proceedings of an expert workshop convened by the U.S. Department of Energy and Industry Canada, and hosted by the National Renewable Energy Laboratory and the California Air Resources Board, May 14-15, 2014, in Sacramento, California, to address the topic of hydrogen energy storage (HES). HES systems provide multiple opportunities to increase the resilience and improve the economics of energy sup supply systems underlying the electric grid, gas pipeline systems, and transportation fuels. This is especially the case when considering particular social goals and market drivers, such as reducing carbon emissions, increasing reliability of supply, and reducing consumption of conventional petroleum fuels. This report compiles feedback collected during the workshop, which focused on policy and regulatory issues related to HES systems. Report sections include an introduction to HES pathways, market demand, and the "smart gas" concept; an overview of the workshop structure; and summary results from panel presentations and breakout groups.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0450.013

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 head0.021
GPT teacher head0.261
Teacher spread0.240 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2015
Admission routes1
Has abstractyes

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