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Record W1575589989 · doi:10.1002/atr.189

About the possibilities of using the renewable energy power sources on railway transport

2011· article· en· W1575589989 on OpenAlexvenueno aff
P. Vorobiev, Yuri V. Vorobiev

Bibliographic record

VenueJournal of Advanced Transportation · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsElectrificationRenewable energyTrainPhotovoltaic systemCompensation (psychology)Solar energyConvertersAutomotive engineeringPower (physics)Solar powerEnergy (signal processing)Environmental scienceEngineeringComputer scienceElectrical engineeringElectricityVoltage

Abstract

fetched live from OpenAlex

SUMMARY Several electrification systems based on renewable energy power sources (first of all, solar energy) are discussed in respect to their applicability to railway transport and, in particular, to suburban electric trains. Two systems are considered with basic technical details and economic estimation, both including the onboard bank of batteries and the photovoltaic converters (PVC) of solar energy for compensation of energy expenses, which could be positioned either on stations or on wagon's roofs. Sun‐tracking systems and their effect on the solar energy conversion efficiency are discussed in application to stationary and moving PVC platforms. An analysis made shows that introduction of the “green” systems discussed will not only have positive ecological impact, but also can bring a notable economical effect even with today's components, while it could be considerably greater with the usage of new PVCs, which are being developed by the authors. Copyright © 2011 John Wiley & Sons, Ltd.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.015
GPT teacher head0.225
Teacher spread0.211 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations15
Published2011
Admission routes1
Has abstractyes

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