Evidence map›Paper›PMID 29467794›Full record

ArticleFrontiers in genetics2018

Detection of Potential Problematic

Xiaobing Li, Xuejuan Shen, Xiao Chen, Dan Xiang, Robert W Murphy, Yongyi Shen

Abstract read
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  16. Foods (Basel, Switzerland) · 2021
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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

6 authors.

Xiaobing LiCollege of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Xuejuan ShenCollege of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Xiao ChenCollege of Marine Sciences, South China Agricultural University, Guangzhou, China.
Dan XiangJoint Influenza Research Centre (SUMC/HKU), Shantou University Medical College, Shantou, China.
Robert W MurphyCentre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, ON, Canada.
Yongyi ShenCollege of Veterinary Medicine, South China Agricultural University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fishes are, by far, the most diverse group of vertebrates. Their classification relies heavily on morphology. In practice, the correct morphological identification of species often depends on personal experience because many species vary in their body shape, color and other external characters. Thus, the identification of a species may be prone to errors. Due to the rapid development of molecular biology, the number of sequences of fishes deposited in GenBank has grown explosively. These published data likely contain errors owing to invalid or incorrectly identified species. The erroneous data can lead to downstream problems. Thus, it is critical that such errors get identified and corrected. A strategy based on DNA barcoding can detect potentially erroneous data, especially when intraspecific K2P variation exceeds interspecific K2P divergence. Analyses of the most used DNA marker for fishes (mitochondrial

Indexed as

CytbDNA barcodingfishGenBanksequence error

Identifiers

PMID29467794
PMCPMC5808227

What OpenQuestion holds

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Registered trials

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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.