Evidence map›Paper›PMID 42004004›Full record

ArticleEco-Environment & Health2026

On the makeup of high-impact reviews in ecology.

Stavros D Veresoglou, Evgenios Agathokleous

Abstract read
In one paragraph

Article in Eco-Environment & Health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Stavros D VeresoglouState Key Laboratory of Biocontrol, School of Ecology, Sun Yat-sen University, Shenzhen 518107, China.
Evgenios AgathokleousClimate and Atmosphere Research Center, The Cyprus Institute, 20 Konstantinou Kavafi Street, Nicosia 2121, Cyprus.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To maximize the impact of our contributions, we strive to perfect our scientific writing. Much of the existing guidance on how to effectively structure reviews originates from anecdotal opinions and guidelines set out by the journals themselves. This makes it less clear what ultimately determines the number of citations of review papers. Citation frequencies partly depend on the topic of the review, and on the innovative nature of the ideas within the review. However, the language norms and the narrative flow within a review might also play an important role in the eventual acceptance of the ideas. Here, we analyzed the text of review papers published in 2020 in the top ten journals in ecology. Citation counts correlated with two of the four psychometrics tested, as well as the word count of the contributions, explaining an aggregate of 1.9% of total variation. We further observed relationships in citation counts with two descriptors of the article structure. We identify linguistic traits correlated with citation frequency in ecology, with potential relevance across other disciplines. A solid theoretical background on best practices in review writing would be transformative in terms of contributing to tools for further improving the impact of reviews, but also to assist their preliminary editorial evaluation.

Indexed as

Computerized text analysisEcology and EvolutionNarrative arcPsychometricsScientific writing

Identifiers

PMID42004004
PMCPMC13087775

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.