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Record W4200415286 · doi:10.18280/ijsdp.160815

Optimal Urban Logistics - Through the Choice of Sustainable Axes

2021· article· en· W4200415286 on OpenAlexvenueno aff
Fadwa Farchi, Badr Touzi, Chayma Farchi, Charif Mabrouki

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2021
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsCity logisticsSustainabilityBusinessUrbanizationZoningOrder (exchange)Environmental planningSustainable cityUrban planningGlobalizationSustainable developmentEnvironmental economicsComputer scienceTransport engineeringEconomicsEngineeringCivil engineeringEconomic growthGeographyPolitical science

Abstract

fetched live from OpenAlex

In a world where urbanization is becoming more and more widespread, big figures can be seen around internal urban migration further aggravating the environmental urban situation, which results from several previous factors. This is the case with globalization, online shopping, or polluting industrial and human sources. The major solutions are centered primarily on the concern for urban mobility, the involvement of the stakeholders concerned, the optimization of journeys, the use of lanes and roads, the choice of vehicles as well as the zoning or choice of logistics locations. Sustainability is one of the primary elements of flow management; it is one of the most important pillars of the concept of "urban logistics". Indeed, the final goal goes beyond the delivery of goods, going so far as to place the environment as an essential support for urban logistics. In this paper we present a literature review on sustainable logistics, we will try to answer the following problem: Urban logistics: Where are we? To respond to this problem, we are taking the following approach: Presentation of the basic concepts, choice of articles to be used for the study which will induce us to determine the axes and the main actors, with the aim of specifying the most predominant aspects which must be treated and prioritized in order to make urban logistics more optimal.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.401

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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