ArticleBiology methods & protocols2020
Optimizing digitalization effort in morphometrics.
Article in Biology methods & protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 30 citations in OpenAlex.
- Bony labyrinth taxonomic identification and long-term evolution of livestock in the Southwest and Central Asia.Royal Society open science · 2026Article
- Landmark-based morphometrics with fewer landmarks: Some examples for medical entomology.PLoS neglected tropical diseases · 2026Article
- Application of the OliveID morphometric tool for the identification of archaeobotanical carbonized olive endocarps: evidence for morphological continuity with the modern Throumbolia cultivar.Frontiers in plant science · 2026Article
- "Visiting scientist effect"? Exploring the impact of time-lags in the digitization of 2D landmark data.Anatomical record (Hoboken, N.J. : 2007) · 2025Article
- Inter- and intra-observer variation in phytolith morphometry.Annals of botany · 2025Article
- Article
- Quantifying the Selection of Maxillary Anterior Teeth Using Extraoral Anatomical Landmarks.Cureus · 2022Article
- Incongruences between morphology and molecular phylogeny provide an insight into the diversification of the Crocidura poensis species complex.Scientific reports · 2022Article
- Can morphotaxa be assessed with photographs? Estimating the accuracy of two-dimensional cranial geometric morphometrics for the study of threatened populations of African monkeys.Anatomical record (Hoboken, N.J. : 2007) · 2022Article
- Automated landmarking via multiple templates.PloS one · 2022Article
- Testing inter-observer error under a collaborative research framework for studying lithic shape variability.Archaeological and anthropological sciences · 2022Article
- Morphology of facial aging: a shape-based quantification.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying phenotypes is a common practice for addressing questions regarding morphological variation. The time dedicated to data acquisition can vary greatly depending on methods and on the required quantity of information. Optimizing digitization effort can be done either by pooling datasets among users, by automatizing data collection, or by reducing the number of measurements. Pooling datasets among users is not without risk since potential errors arising from multiple operators in data acquisition prevent combining morphometric datasets. We present an analytical workflow to estimate within and among operator biases and to assess whether morphometric datasets can be pooled. We show that pooling and sharing data requires careful examination of the errors occurring during data acquisition, that the choice of morphometric approach influences amount of error, and that in some cases pooling data should be avoided. The demonstration is based on a worked example (
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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.