Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 964

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

The campaign to DNA barcode all fishes, FISH‐BOL

Ward, R. D., Hanner, R., Hebert, P. D. N.·2009·Journal of Fish Biology

Abstract

FISH‐BOL, the Fish Barcode of Life campaign, is an international research collaboration that is assembling a standardized reference DNA sequence library for all fishes. Analysis is targeting a 648 base pair region of the mitochondrial cytochrome c oxidase I (COI) gene. More than 5000 species have already been DNA barcoded, with an average of five specimens per species, typically vouchers with authoritative identifications. The barcode sequence from any fish, fillet, fin, egg or larva can be matched against these reference sequences using BOLD; the Barcode of Life Data System (http://www.barcodinglife.org). The benefits of barcoding fishes include facilitating species identification, highlighting cases of range expansion for known species, flagging previously overlooked species and enabling identifications where traditional methods cannot be applied. Results thus far indicate that barcodes separate c.98 and 93% of already described marine and freshwater fish species, respectively. Several specimens with divergent barcode sequences have been confirmed by integrative taxonomic analysis as new species. Past concerns in relation to the use of fish barcoding for species discrimination are discussed. These include hybridization, recent radiations, regional differentiation in barcode sequences and nuclear copies of the barcode region. However, current results indicate these issues are of little concern for the great majority of specimens.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/j.1095-8649.2008.02080.x

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Metadata

Authors
Ward, R. D., Hanner, R., & Hebert, P. D. N.
Venue
Journal of Fish Biology
Publisher
Wiley
Published
2009-01-29
Volume
74
Issue
2
Pages
329-356
ISSN
  • 0022-1112 (ISSN-L)
  • 1095-8649
OpenAlex
W2111456242
Cited by
964
References
3
FWCI
46.86
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.