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Record W3135792803

CITYLAB Deliverable 2.1, Observatory of Strategic Developments Impacting Urban Logistics (2018 version)

2018· preprint· en· W3135792803 on OpenAlexaff
Lætitia Dablanc, Josselin Rouhier, Nicolas Lazarevic, Jens Klauenberg, Zeting Liu, Martin Koning, Leise Kelli de Oliveira, François Combes, Nicolas Coulombel, Mathieu Gardrat, Corinne Blanquart, Adeline Heitz, Saskia Seidel

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2018
Typepreprint
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsDeliverableObservatoryBusinessOperations managementEngineeringSystems engineeringPhysicsAstronomy
DOInot available

Abstract

fetched live from OpenAlex

This research report is an end product of the European H2020 project CITYLAB (2013-2018). Urban freight living labs need to operate in full recognition of the challenges that will shape the mobility of goods in urban areas in the future. These challenges are several: macro-economic, micro-economic, demographic, technological, societal, and legal. To help CITYLAB cities implement their urban freight initiatives, a better understanding of these challenges is necessary. This is what this Observatory of strategic developments impacting urban logistics intends to do, by providing data and analysis on some of the most important, or less well known, trends that will shape the urban mobility of goods in the future.This third version (2018) of the Observatory provides data and analyses on 1) Logistics Sprawl; 2) E-commerce; 3) Service trips; and 4) Circular economy.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.241
Threshold uncertainty score0.807

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0060.005
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2410.192

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 head0.050
GPT teacher head0.213
Teacher spread0.163 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2018
Admission routes1
Has abstractyes

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