Evidence map›Paper›PMID 33846509›Full record

ArticleScientific reports2021

Statistical characterization of airplane delays.

Evangelos Mitsokapas, Benjamin Schäfer, Rosemary J Harris, Christian Beck

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Functional connectivity networks for transportation delay analysis: From theory to software.Transportation research interdisciplinary perspectives · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Evangelos Mitsokapas *School of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK.
Benjamin Schäfer *School of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK. b.schaefer@qmul.ac.uk.
Rosemary J HarrisSchool of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK.
Christian BeckSchool of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK.

Funding

H2020 Marie Sklodowska-Curie Actions 840825
6 · The paper itself

Abstract

The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.

Identifiers

PMID33846509
PMCPMC8041857

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.