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Record W581470350

Metrolinx: Governing the Growth of Transportation in Canada's Largest Urban Region

2009· article· en· W581470350 on OpenAlexaboutno aff
Gary McNeil

Bibliographic record

VenuePublic transport international · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsTRIPS architecturePlan (archaeology)Transit (satellite)Work (physics)Transport engineeringTransportation planningAgency (philosophy)Investment (military)Public transportBusinessGovernment (linguistics)Rail transitJourney to workRegional planningEnvironmental planningUrban planningGeographyEngineeringPolitical scienceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

The Greater Toronto and Hamilton area (GTHA) is the mostly densely populated and fastest-growing region in Canada. However, the regional transportation infrastructure has not expanded with this growth, with 75% of daily trips taken in cars. This article describes how a new transportation agency called Metrolinx is hoping to change this. Metrolinx was formed by the provincial government to serve as the organizing body for transportation in the GTHA. Metrolinx's objective is to lead policy, planning and financing for seamless interregional travel in the GTHA. Metrolinx also operates the interregional transit system in the area. Metrolinx recently released a 25-year regional transportation plan. The plan calls for a network of expanded rapid transit connecting community-oriented mobility hubs that link transit to places where people live, work and play. With this plan, 50% more residents will live and work within two kilometers of rapid transit. The plan also calls for investment in walking and cycling facilities.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.361

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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 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
Published2009
Admission routes1
Has abstractyes

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