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Record W2412151726 · doi:10.13189/aeb.2016.040603

Economic Evaluation of Climate Change Impacts on Road Transportation in Atlantic Canada

2016· article· en· W2412151726 on OpenAlexaffabout
Yuri Yevdokimov

Bibliographic record

VenueAdvances in Economics and Business · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsClimate changeEconomic impact analysisEnvironmental resource managementNatural resource economicsGeographyBusinessEnvironmental scienceEconomicsOceanographyEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Climate change impacts such as an increase in mean temperature, change in precipitation patterns and sea level rise are affecting regional road transportation network in Atlantic Canada. Those impacts cause direct and indirect economic consequences for the network and regional economy. In our study, we constructed a dynamic computable general equilibrium model (CGEM) to trace these consequences over time. Basic principles of the designed CGEM are discussed and the model's architecture is presented. The model's elements are estimated, and the obtained CGEM is tested with exogenously imposed shocks. The dynamics of regional temperature, precipitation and sea level are analyzed on the basis of comprehensive time series analysis. This dynamics will later be imposed on the designed CGEM as external productivity shocks. Some preliminary cumulative economic consequences are evaluated in monetary terms to obtain benchmarks for the mitigation measures associated with future development of the regional road transportation network.

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 score0.758
Threshold uncertainty score0.787

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 communication0.0000.001
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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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
Published2016
Admission routes2
Has abstractyes

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