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Record W643766966

2008-2012 Infrastructure Needs for Canadian Transit Systems

2008· article· en· W643766966 on OpenAlexaboutno aff
Colleen M. Norris

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessLiberian dollarTransport engineeringInvestment (military)Transit (satellite)Bus rapid transitTaxisPromotion (chess)Public transportFinanceCapital expenditurePopulationEngineering
DOInot available

Abstract

fetched live from OpenAlex

The fifth edition of the Canadian Urban Transit Association's (CUTA) transit infrastructure needs survey has estimated the infrastructure requirements of transit systems across the country to be $40.1 billion for the period 2008-2012. Canada's infrastructure needs over the period include bus, subway, LRT and commuter car purchases and refurbishment, development and construction of fixed guideways and rights-of-way such as BRT and LRT, new and improved maintenance facilities, stations and terminals, new park and ride facilities, the implementation of transit priority measures, new customer amenities. Transit systems were asked to list their budgeted capital infrastructure needs for the next five years (2008-2012) by dollar value. These were categorized by expenditures for replacement or rehabilitation, expenditures for expansion in response to population growth or promotion of new ridership; expenditures currently planned (under existing funding programs) and additional needs that can only be met through new external investment. Currently many transit systems are operating at or beyond their design capacity, and some systems are facing significant latent demand that cannot be satisfied without major investment in service improvement and capacity expansion.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.995

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 head0.006
GPT teacher head0.175
Teacher spread0.169 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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