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Record W4401812800 · doi:10.55016/ojs/sppp.v14i1.70156

Constraints in the Canadian Transport Infrastructure Grid

2021· article· en· W4401812800 on OpenAlexfundaboutno aff
Jean‐Paul Rodrigue

Bibliographic record

VenueThe School of Public Policy Publications · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsGridTransport infrastructureBusinessComputer scienceEnvironmental planningTransport engineeringEnvironmental scienceGeographyEngineeringGeodesy

Abstract

fetched live from OpenAlex

The corridor concept aims at reducing the costs, duplication, and delays associated with the construction of transportation and ancillary infrastructure. These include diversification of export markets, supporting indigenous and northern development, expanding interregional and international trade, enhancing northern security and relieving bottlenecks and constraints to the existing transportation infrastructure grid. In support of the Canadian Northern Corridor research agenda, the purpose of this study is to compile a review and evaluation of the constraints impairing the Canadian transport infrastructure grid. It identifies and evaluates the existing and expected bottlenecks and constraints in terminals (ports and airports), connectors (road, rail, and pipelines), and ancillary infrastructure (power transmission and telecommunications). It also outlines the opportunities and constraints for infrastructure development in a potential corridor.

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)0.010
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: Empirical · Consensus signal: none
Teacher disagreement score0.107
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.016
Science and technology studies0.0070.003
Scholarly communication0.0110.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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