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Record W4319985834 · doi:10.1088/978-0-7503-5306-9

Transportation Technologies for a Sustainable Future

2023· book· en· W4319985834 on OpenAlexaff
R. A. Dunlap

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBusinessEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

Transportation is a major contributor to greenhouse gas emissions. Any long-term plan to reduce, and eventually eliminate, fossil fuel use needs to include a transitioning of transportation energy to low-carbon sustainable sources. This book outlines the current transportation energy requirements and the primary sources of this energy. A detailed analysis of technologies appropriate for road transportation is included, and the application of sustainable technologies to rail, maritime and air transportation is discussed. Finally, a summary of the challenges involved in implementing sustainable transportation technologies and a quantitative analysis of how renewable energy production relates to the development of sustainable transportation are presented. The book is an invaluable reference for undergraduate and postgraduate science and engineering students with an interest in energy, transportation or environmental issues. Part of <a href="https://iopscience.iop.org/bookListInfo/iop-series-in-renewable-and-sustainable-power#series">IOP Series in Renewable and Sustainable Power</a>. Key features • Reviews the energy technologies that may be appropriate for future transportation needs. • Considers resource and environmental reasons for changing our approach to energy, as well as possible future energy sources and future energy needs. • Describes the scientific basis and application of all major technologies for road, rail, maritime and air transportation. • Provides a detailed quantitative analysis of the way in which future transportation energy can be integrated into global sustainable energy production. • Summarises the challenges involved in implementing sustainable transportation technologies.

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 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: Other · Consensus signal: Other
Teacher disagreement score0.575
Threshold uncertainty score0.724

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 head0.008
GPT teacher head0.217
Teacher spread0.208 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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