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Record W2241924265

Sustainable Mobility of Small Tourist Places

2014· article· en· W2241924265 on OpenAlexaff
Mario Njegovec, Luka Kosmat

Bibliographic record

VenueProceedings of the International Conference on Road and Rail Infrastructure CETRA · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsTransport Canada
Fundersnot available
KeywordsTourismEnvironmental economicsAttractivenessBusinessTransport engineeringSustainable developmentGreenhouse gasPopulationEnvironmental planningConsumption (sociology)Sustainable transportPublic transportSustainabilityGeographyEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

Article describes the development of a strategic plan of sustainable mobility of the Municipality Lopar on the Rab Island. In small tourist places number of tourists greatly exceeds the number of the local population during the tourist season. Via the integration, participation and evaluation principles existing plans are upgrading. Scenarios of transport system were developed by the analysis of the shortcomings and the introduction of the measures as a whole. Evaluation scenarios were based on ensure the accessibility offered by the transport system to all, improve safety and security, reduce air and nois pollution, greenhouse gas emission and energy consumption, improve the efficiency and cost-effectiveness of the transportation of person and goods, contribute to enhancing the attractiveness and quality of the municipality environment and design. Finally, the proposed measures are necessary, measures to improve, measures of scenarios for each of the reference year to which examines traffic.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Road and Rail Infrastructure CETRASame topicTransportation Planning and OptimizationFrench-language works237,207