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Record W4386855868 · doi:10.1139/cjce-2023-0187

Resilience for freight transportation systems to disruptive events: a review of concepts and metrics

2023· review· en· W4386855868 on OpenAlexafffundvenue
Phani Kumar Patnala, Jonathan D. Regehr, Babak Mehran, Chaouki Regoui

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2023
Typereview
Languageen
FieldEngineering
TopicInfrastructure Resilience and Vulnerability Analysis
Canadian institutionsNational Research Council CanadaUniversity of Manitoba
FundersNational Research Council Canada
KeywordsInterdependenceResilience (materials science)Context (archaeology)Perspective (graphical)Multidisciplinary approachComputer scienceRisk analysis (engineering)Process managementManagement scienceEngineeringBusinessSociologyGeography

Abstract

fetched live from OpenAlex

Resilience is a multidisciplinary concept that deals with rapid response and recovery of a system experiencing a disruption. Despite extensive research on this topic, there is a need to clarify resilience concepts in the context of road freight transportation systems (FTSs) from a three-dimensional perspective (i.e., physical infrastructure, users, and managing organizations) and to identify persistent knowledge gaps concerning the characterization and measurement of FTS resilience vis-à-vis disruptive events. This paper addresses these shortcomings through a systematic review of 149 research studies. The synthesis of findings clarifies inconsistencies associated with the characteristics of FTS resilience and in so doing, establishes a unified framework for measuring FTS resilience through the life cycle of disruptive events. Critical data gaps, methodological shortcomings, and a lack of empirical evidence concerning FTS resilience to disruptive events remain. More robust analytical approaches are required to incorporate interdependencies among FTS dimensions into resilience assessments.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.288
Teacher spread0.267 · 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.

Study designSystematic review
Domainnot available
GenreReview

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
Published2023
Admission routes3
Has abstractyes

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