Evidence map›Paper›PMID 41083593›Full record

ArticleScientific reports2025

Corrected population grid data using multisource high precision data.

Shuang Wang, Chun Dong, Rong Zhao, Yu Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. 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

4 authors.

Shuang WangChinese Academy of Surveying and Mapping, Beijing, China.
Chun DongChinese Academy of Surveying and Mapping, Beijing, China. dongchun@casm.ac.cn.
Rong ZhaoChinese Academy of Surveying and Mapping, Beijing, China.
Yu ZhangChinese Academy of Surveying and Mapping, Beijing, China.

Funding

COMPREHENSIVE OUTCOME OF NONMELANOMA SKIN CANCERK02AR002203 · NIAMS · UNIVERSITY OF CALIFORNIA SAN FRANCISCO · PI CHREN, MARY-MARGARET · 2001 to 2005
$436k
Chinese Academy of Surveying and Mapping AR2203National Natural Science Foundation of China 71903183NIAMS NIH HHS K02 AR002203
6 · The paper itself

Abstract

Population grid data provide a fundamental scientific basis for ecological planning and management, environmental monitoring and assessment, ecological early warning, and emergency response. Traditional population allocation methods based on administrative units frequently introduce cross-scale errors, and current population grid datasets require enhancement regarding regional fine-grained characteristics and population distribution. This study presents a methodology to correct public population grid data utilizing Multisource high precision data at the grid scale. WorldPop serves as the baseline data for correction. The original data undergoes enhancement through a new model, incorporating Multisource high precision auxiliary data. The results indicate that compared to the original data, the RMSE of the corrected population grid data decreased by more than seven times, with an R

Indexed as

Corrected populationHigh precision geographicMultisource dataPopulation gridPublic population gridWorldPop

Identifiers

PMID41083593
PMCPMC12518877

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.