Evidence map›Paper›PMID 41394183›Full record

ArticleEcology and evolution2025

Refining Uniform Discrimination Metrics: Towards a Case-by-Case Weighting Evaluation in Species Distribution Models With Presence-Absence Data.

Alberto Jiménez-Valverde

Abstract read
In one paragraph

Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

1 author.

Alberto Jiménez-ValverdeDepartment of Biogeography and Global Change Museo Nacional de Ciencias Naturales (MNCN), CSIC Madrid Spain.ORCID https://orcid.org/0000-0001-9962-2106

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species distribution models are widely used in ecological research, but their validation remains challenging due to the representative effect. This effect, which reflects the strong dependence of discrimination performance on the distribution of suitability values, hampers the comparison and generalization of discrimination statistics across datasets. This study aims to address this issue by refining uniform discrimination metrics (e.g.,

Indexed as

ecological niche modelsevaluationpresence‐absence modelsrepresentativeness effectROC analysissensitivity‐star

Identifiers

PMID41394183
PMCPMC12698938

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.