Evidence map›Paper›PMID 37011048›Full record

ArticlePloS one2023

Examining the extraction of parafoveal semantic information in Tibetan.

Meng Shen, Zibei Niu, Lei Gao, Tianzhi Li, Danhui Wang, Shan Li, Man Zeng, Xuejun Bai, Xiaolei Gao

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Meng ShenPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Zibei NiuPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Lei GaoPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Tianzhi LiPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Danhui WangPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Shan LiPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Man ZengPlateau Brain Science Research Center, Tibet University, Lhasa, China.
Xuejun BaiKey Research Base of Humanities and Social Sciences, Institute of Psychology and Behavior, Tianjin Normal University, Tianjin, China.
Xiaolei GaoPlateau Brain Science Research Center, Tibet University, Lhasa, China.ORCID 0000-0002-1041-8705

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study conducted two experiments to investigate the extraction of semantic preview information from the parafovea in Tibetan reading. In Experiment 1, a single-factor (preview type: identical vs. semantically related vs. unrelated) within-subject experimental design was used to investigate whether there is a parafoveal semantic preview effect (SPE) in Tibetan reading. Experiment 2 used a 2 (contextual constraint: high vs. low) × 3 (preview type: identical vs. semantically related vs. unrelated) within-subject experimental design to investigate the influence of contextual constraint on the parafoveal semantic preview effect in Tibetan reading. Supporting the E-Z reader model, the experimental results showed that in Tibetan reading, readers could not obtain semantic preview information from the parafovea, and contextual constraint did not influence this process. However, comparing high- and low-constrained contexts, the latter might be more conducive to extracting semantic preview information from the parafovea.

Indexed as

Eye MovementsSemanticsFixation, OcularFovea CentralisPattern Recognition, VisualReadingResearch DesignTibet

Identifiers

PMID37011048
PMCPMC10069765

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.