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Record W657034745

Toronto's Rail Systems are Pushed to Perform

2007· article· en· W657034745 on OpenAlexaboutno aff
Ernst H Robl

Bibliographic record

VenueMetrologia · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsTransit (satellite)TrainCrewTRIPS architectureTransport engineeringTransit systemTrack (disk drive)Rail transitBusinessTelecommunicationsPublic transportGeographyAeronauticsEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Toronto's two rail transit providers are in the midst of upgrades and expansions to cope with growth in Canada's largest city and financial center. Historically a heavy transit use area, behind only New York City and Mexico City in terms of North American transit ridership, Toronto is home to the Toronto Transit Commission (TTC) and Go Transit (the Greater Toronto Transit Authority), which together provide more than 500 million passenger trips each year. TTC predates most other major North American systems, and GO Transit is known for having established benchmarks for regional commuter rail transit. Its signature innovation was adoption of lozenge cars from Bombardier, which are double-decker in the middle and single story at each end, permitting push-pull traction and easy communication between cars of different heights and engines for crew and passengers. While capacity needs to be expanded, conflicts with the Canadian Northern and Canadian Pacific freight railroads over track rights need to be resolved. One hopeful development is an advanced signal technology permitting greater use of existing tracks by both freight and commuter trains.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.216
Teacher spread0.198 · 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.

Study designObservational
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

Citations0
Published2007
Admission routes1
Has abstractyes

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