ArticleEcology and evolution2022
Influence of different data cleaning solutions of point-occurrence records on downstream macroecological diversity models.
Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
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Who cites it
4 citing papers in PubMed.
- Diversity and Distribution Patterns of Insects in Nigeria: A GBIF-Based Appraisal.Ecology and evolution · 2026Article
- Article
- A dataset of cold-water coral distribution records.Data in brief · 2023Article
- Influence of different data cleaning solutions of point-occurrence records on downstream macroecological diversity models.Ecology and evolution · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital point-occurrence records from the Global Biodiversity Information Facility (GBIF) and other data providers enable a wide range of research in macroecology and biogeography. However, data errors may hamper immediate use. Manual data cleaning is time-consuming and often unfeasible, given that the databases may contain thousands or millions of records. Automated data cleaning pipelines are therefore of high importance. Taking North American
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Registered trials
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