Evidence map›Paper›PMID 29942695›Full record

ArticlePeerJ2018

Low resolution scans can provide a sufficiently accurate, cost- and time-effective alternative to high resolution scans for 3D shape analyses.

Ariel E Marcy, Carmelo Fruciano, Matthew J Phillips, Karine Mardon, Vera Weisbecker

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
11.9field-weighted citation impact, top 1% of its field
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

18 citing papers in PubMed, 53 citations in OpenAlex.

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  15. First record of disk-footed batZoological research · 2021
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  18. A Practical Guide to Sliding and Surface Semilandmarks in Morphometric Analyses.Integrative organismal biology (Oxford, England) · 2019
    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

5 authors at 3 institutions in 2 countries.

Ariel E MarcySchool of Biological Sciences, University of Queensland, Brisbane, Queensland, Australia.
Carmelo FrucianoInstitut de biologie de l'Ecole normale supérieure, Ecole normale supérieure, Université Paris, Paris, France.
Matthew J PhillipsSchool of Earth, Environmental and Biological Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Karine MardonCentre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.
Vera WeisbeckerSchool of Biological Sciences, University of Queensland, Brisbane, Queensland, Australia.
University of Queensland · AUInstitut de Biologie de l'École Normale Supérieure · FRQueensland University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvances in 3D shape capture technology have made powerful shape analyses, such as geometric morphometrics, more feasible. While the highly accurate micro-computed tomography (µCT) scanners have been the "gold standard," recent improvements in 3D surface scanners may make this technology a faster, portable, and cost-effective alternative. Several studies have already compared the two devices but all use relatively large specimens such as human crania. Here we perform shape analyses on Australia's smallest rodent to test whether a 3D scanner produces similar results to a µCT scanner.

methodsWe captured 19 delicate mouse (

resultsIn all Procrustes ANOVAs, regardless of factors included, differences between individuals contributed the most to total variation. The PCA plots reflect this in how the individuals are dispersed. Including only the symmetric component of shape increased the biological signal relative to variation due to device and due to error. 3D scans showed a higher level of operator error as evidenced by a greater spread of their replicates on the PCA, a higher level of multivariate variation, and a lower repeatability score. However, the 3D scan and µCT scan datasets performed identically in classifying individuals based on intra-specific patterns of sexual dimorphism. DISCUSSION: Compared to µCT scans, we find that even low resolution 3D scans of very small specimens are sufficiently accurate to classify intra-specific differences. We also make three recommendations for best use of low resolution data. First, we recommend that extreme caution should be taken when analyzing the asymmetric component of shape variation. Second, using 3D scans generates more random error due to increased landmarking difficulty, therefore users should be conservative in landmark choice and avoid multiple operators. Third, using 3D scans introduces a source of systematic error relative to µCT scans, therefore we recommend not combining them when possible, especially in studies expecting little biological variation. Our findings support increased use of low resolution 3D scans for most morphological studies; they are likely also applicable to low resolution scans of large specimens made in a medical CT scanner. As most vertebrates are relatively small, we anticipate our results will bolster more researchers in designing affordable large scale studies on small specimens with 3D surface scanners.

Indexed as

Generalized procrustes analysisGeometric morphometricsGeomorphPhotogrammetryPseudomys delicatulusRandom errorShape variationSystematic error

Identifiers

PMID29942695
PMCPMC6016532
OpenAlexW2809530760

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.