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Record W777746412

Better rail stations

2009· article· en· W777746412 on OpenAlexaboutno aff
C Green, Peter Hall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsInterimFranchiseTransport engineeringBusinessQuarter (Canadian coin)State (computer science)Computer scienceEngineeringGeographyMarketing
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a review of the state of UK railway stations and recommendations for short- and long-term improvements. Only two-thirds of travellers are satisfied with station facilities. However, additional funding will be very limited up to 2014, and the authors propose that minimum standards should be introduced in every new franchise in the interim, with funding directed to priority cases. Key recommendations include minimum standards for each of six station categories. Ten interchange stations are proposed for priority funding. The spending rate on station improvement should be increased by a quarter for the period 2014-2024. Better access to stations is needed with the creation of cycle and car parking. Stations should be planned as transport hubs to involve local communities and other transport operators.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.071
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0710.014

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 head0.201
Teacher spread0.186 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

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