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Record W640449961

When will Japan Choose Light Rail Transit

2004· article· en· W640449961 on OpenAlexaboutno aff
Kiyohito Utsunomiya

Bibliographic record

VenueJRTR. Japan railway & transport review · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsLight rail transitLight railPublic transportTransport engineeringTransit systemRapid transitTransit (satellite)Bus rapid transitBusinessEngineering
DOInot available

Abstract

fetched live from OpenAlex

Interest in Light Rail Transit (LRT) as a viable urban transportation system has been growing worldwide since the late 20th century. Although there is no definite difference between trams and LRT systems, the latter is an evolved tramway system—tracks are often segregated from other traffic, cars run faster, and everyone has easy access due to level boarding. In Germany, where old tramway systems have been vigorously upgraded as LRT (Stadtbahn) systems since the 1960s, LRT systems have become the core of urban transport in many cities. Also new LRT systems have been constructed in France and the UK some 40 or so years after both countries closed many old tramway systems dating from the Victorian era. LRT systems are also starting to appear in the USA and Canada, two countries known for their love of the automobile. Under these circumstances, although no new LRT systems have been built in Japan recently, some tramway systems have begun to introduce low-floor cars with improved ease-of-access and efficiency. This article reviews Japanese tramway systems and discusses the possibility of reviving them as LRT systems. Short History of Tramways in Japan

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0000.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0260.013

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 head0.019
GPT teacher head0.285
Teacher spread0.265 · 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
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

Citations1
Published2004
Admission routes1
Has abstractyes

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