MétaCan
Menu
Back to cohort
Record W4255326545 · doi:10.1002/9781119713173.ch2

Energy Storage Systems

2021· other· en· W4255326545 on OpenAlexaff
İbrahim Dinçer, Marc A. Rosen

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsEnergy storageThermal energy storageElectricityPumped-storage hydroelectricityEnergy (signal processing)Thermal energyEnvironmental scienceProcess engineeringEnergy recoveryEnergy engineeringRenewable energyEngineeringDistributed generationElectrical engineeringEcology

Abstract

fetched live from OpenAlex

Energy storage (ES) is critically important to the success of any intermittent energy source in meeting demand. ES systems can contribute significantly to meeting society's needs for more efficient, environmentally benign energy use in building heating and cooling, transportation, and utility applications. Mechanical and hydraulic ES systems usually store energy by converting electricity into energy of compression, elevation, or rotation. New storage technologies may facilitate the development of electric-powered automobiles. Biological storage is the storage of energy in chemical form by means of biological processes and is considered an important method of storage for long periods of time. Thermal energy storage can be an important means of offsetting the mismatch between thermal energy availability and demand. Hydrogen has advantages and disadvantages as a medium for storing energy. Anticipated patterns of future energy use and consequent environmental impacts are comprehensively discussed.

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)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0680.030

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 head0.014
GPT teacher head0.246
Teacher spread0.231 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Battery Technologies ResearchFrench-language works237,207