Evidence map›Paper›PMID 39789040›Full record

ArticleScientific data2025

Global Crop-Specific Fertilization Dataset from 1961-2019.

Fernando Coello, Thomas Decorte, Iris Janssens, Steven Mortier, Jordi Sardans, Josep Peñuelas, Tim Verdonck

Erratum issuedAbstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Fernando Coello *Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. f.coello@creaf.uab.cat.ORCID http://orcid.org/0000-0001-9466-8009
Thomas Decorte *University of Antwerp - imec - IDLab, Department of Mathematics, Antwerp, 2000, Belgium. thomas.decorte@uantwerpen.be.
Iris JanssensUniversity of Antwerp - imec - IDLab, Department of Computer Science, Antwerp, 2000, Belgium.ORCID http://orcid.org/0000-0003-2961-8341
Steven MortierUniversity of Antwerp - imec - IDLab, Department of Computer Science, Antwerp, 2000, Belgium.ORCID http://orcid.org/0000-0001-8241-6656
Jordi SardansCREAF - Centro de Investigación Ecológica y Aplicaciones Forestales, Barcelona, 08193, Spain.ORCID http://orcid.org/0000-0003-2478-0219
Josep PeñuelasCREAF - Centro de Investigación Ecológica y Aplicaciones Forestales, Barcelona, 08193, Spain.ORCID http://orcid.org/0000-0002-7215-0150
Tim VerdonckUniversity of Antwerp - imec - IDLab, Department of Mathematics, Antwerp, 2000, Belgium.

Funding

European Commission (EC) 964545
6 · The paper itself

Abstract

As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fill existing data gaps by employing two machine learning models, eXtreme Gradient Boosting and HistGradientBoosting algorithms to produce precise country-level predictions of nitrogen (N), phosphorus pentoxide (P

Identifiers

PMID39789040
PMCPMC11718267

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.