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Record W2428274092

Logistics sprawl in the region Zurich

2016· article· en· W2428274092 on OpenAlexaboutno aff
Paolo Todesco, Ulrich Weidmann, Ueli Haefeli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsUrban sprawlBusinessLand useCity logisticsMetropolitan areaTransport engineeringService (business)GeographyAgricultural economicsEngineeringEconomicsMarketingCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

Logistics sprawl is a land use phenomenon, which has been detected in many urban areas around the world (e. g. Paris, Atlanta, Toronto, Los Angeles, and others). It consists in the displacement of logistics sites from urban areas to suburban areas. Logistics sprawl can negatively affect the reliability of deliveries, increase delivery costs and have undesirable environmental effects (emissions, land consumption). Over the last 20 years, Zurich experienced a significant densification of its urban fabric, which potentially fostered the sprawl of the land-intensive logistic sector. Therefore, we analysed the locations of four types of logistic firms (road transportation, storage, courier service, postal service) in the Zurich area in the period of 1995 – 2012 to determine to what degree logistic sprawl occurred in said area and how this affected the distance of the mean delivery route. The analysis shows that the mean distance of the storage and the courier services firms from the Zurich city centre increased significantly. The logistic sprawl did not occur for the road transportation firms and for post offices. To avoid the displacement of logistics firms in suboptimal sites, it is important to proactively locate the best potential logistics sites and secure them by land use regulation.

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: none
Teacher disagreement score0.994
Threshold uncertainty score0.122

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 head0.035
GPT teacher head0.182
Teacher spread0.147 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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