Evidence map›Paper›PMID 38612329›Full record

ArticleAnimals : an open access journal from MDPI2024

New Insights into Geometric Morphometry Applied to Fish Scales for Species Identification.

Francesca Traverso, Stefano Aicardi, Matteo Bozzo, Matteo Zinni, Andrea Amaroli, Loris Galli, Simona Candiani, Stefano Vanin, Sara Ferrando

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Carapace Morphological Characteristics of Chinese Mitten Crab (Animals : an open access journal from MDPI · 2025
    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.

Francesca TraversoDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.
Stefano AicardiDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0003-4284-1097
Matteo BozzoDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0002-7452-3758
Matteo ZinniDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.
Andrea AmaroliDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0002-0494-7942
Loris GalliDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0002-8920-8881
Simona CandianiDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0002-4453-5475
Stefano VaninDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0003-1676-5916
Sara FerrandoDepartment of Earth, Environmental, and Life Sciences, University of Genoa, Corso Europa, 26, 16132 Genoa, Italy.ORCID 0000-0002-5781-9709

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The possibility of quick and cheap recognition of a fish species from a single dermal scale would be interesting in a wide range of contexts. The methods of geometric morphometry appear to be quite promising, although wide studies comparing different approaches are lacking. We aimed to apply two methods of geometric morphometry, landmark-based and outline-based, on a dataset of scales from five different teleost species:

Indexed as

geomorphlandmarkmomocsoutline

Identifiers

PMID38612329
PMCPMC11010809

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.