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Record W1982085667 · doi:10.1115/jrc2008-63010

The TRAXX Platform: A New Way to Build Electric and Diesel Locomotives

2008· article· en· W1982085667 on OpenAlexaff
J. Vitins

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicTransportation Systems and Safety
Canadian institutionsBombardier (Canada)
FundersEuropean Commission
KeywordsStandardizationEngineeringAxleAutomotive engineeringTransport engineeringTraction control systemManufacturing engineeringComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

The opening of the European market for freight and passenger services has initiated the need for cross-border locomotives which fulfill the specific requirements of each country and comply with new European standards. The TRAXX locomotive platform addresses this new market with four locomotive types. Each type is configured with standard building blocks. The TRAXX platform covers both electric and diesel 4-axle locomotives. A high level of standardization allows manufacturing of all types in a single assembly line, thus also reducing manufacturing costs for small production lots. The key to the TRAXX platform is a high level of system integration. Important innovations are in the traction chain, carbody, air supply, in the development of automatic train protection (ATP) systems based on the future European standard ETCS (European Train Control System) and in system integration. Today, the TRAXX platform covers all major mainline traction needs in continental Europe with more than 1′200 locomotives so far sold. Further developments are needed to optimize the ATP systems for new and important cross-border freight corridors and to streamline the homologation procedures throughout Europe.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.016

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 head0.020
GPT teacher head0.226
Teacher spread0.206 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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