MétaCan
Menu
Back to cohort
Record W2785479126 · doi:10.1155/2018/5274789

A Model for the Evaluation of Brazilian Road Transport: A Sustainable Perspective

2018· article· en· W2785479126 on OpenAlexvenueno aff
Mariana Gonçalves de Carvalho Wolff, Marco Antônio Farah Caldas

Bibliographic record

VenueJournal of Advanced Transportation · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityInvestment (military)Sustainable transportRoad transportMode (computer interface)Perspective (graphical)Environmental economicsMode of transportMode choiceTransport engineeringBusinessComputer scienceEconomicsEngineeringPublic transportPolitical science

Abstract

fetched live from OpenAlex

Freight transportation in Brazil is heavily based on the road mode bringing heavy dependence of this mode to the country and some consequences such as high operating costs and high air emissions. For these reasons, it was considered the necessity of evaluating new investments made in this mode from a sustainable perspective, taking into account not only economic but also social and environmental concepts. Towards this purpose, the study develops an evaluation model of road transport infrastructure, the TIM, which will help decision making in situations of choice between different alternatives of road projects. The model includes ten variables that count from the initial investment in the road to air emissions of carbon dioxide. All are monetarized individually and then consolidated into a single equation. The result of applying the model is innovative when considering the three spheres of sustainability to evaluate future road transport projects and rank them.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.038
GPT teacher head0.375
Teacher spread0.337 · 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 designSimulation or modeling
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

Citations19
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Advanced TransportationSame topicUrban Transport and AccessibilityFrench-language works237,207