Evidence map›Paper›PMID 36641531›Full record

ArticleScientific data2023

The database for extracting numerical and visual properties of numerosity processing in the Chinese population.

Dazhi Cheng, Zhijun Cui, Chunhui Chen, Xin Xu, Kai Niu, Zhiqiang He, Xinlin Zhou

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Dazhi ChengState Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875, Beijing, China.ORCID 0000-0002-5570-2240
Zhijun CuiState Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875, Beijing, China.ORCID 0000-0001-5933-5655
Chunhui ChenState Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875, Beijing, China.ORCID 0000-0002-9592-5692
Xin XuLaboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, 100876, Beijing, China.
Kai NiuLaboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, 100876, Beijing, China.
Zhiqiang HeLaboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, 100876, Beijing, China.
Xinlin ZhouState Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875, Beijing, China. zhou_xinlin@bnu.edu.cn.ORCID 0000-0002-3530-0922

Funding

National Natural Science Foundation of China (National Science Foundation of China) 31600896National Natural Science Foundation of China (National Science Foundation of China) 31671151National Natural Science Foundation of China (National Science Foundation of China) 31700977National Natural Science Foundation of China (National Science Foundation of China) 32271122Natural Science Foundation of Beijing Municipality (Beijing Natural Science Foundation) 5212004
6 · The paper itself

Abstract

The ability to handle non-symbolic numerosity has been recurrently linked to mathematical abilities. The accumulated data provide a rich resource that can reflect the underlying properties (i.e., dot ratio, area, convex hull, perimeters, distance, and hash) of numerosity processing. This article reports a database of numerosity processing in the Chinese population. The database contains five independent datasets with 7459, 4902, 415, 671, 414 participants respectively. For each dataset, all data were collected in the same online computerized test, examination room, professorial tester, and using the same protocols. Computational modeling method could be used to extract the dot ratio and visual properties of numerosity from five types of dot stimuli. This database enables researchers to test the theoretical hypotheses regarding numerosity processing using a large sample population. The database can also indicate the individual difference of non-symbolic numerosity in mathematical abilities.

Identifiers

PMID36641531
PMCPMC9840615

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.