Evidence map›Paper›PMID 30151184›Full record

ReviewEcology and evolution2018

X-ray computed tomography and its potential in ecological research: A review of studies and optimization of specimen preparation.

Yeisson Gutiérrez, David Ott, Mareike Töpperwien, Tim Salditt, Christoph Scherber

Open access · goldAbstract readReview
In one paragraph

Review in Ecology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Deep-LSTM ensemble framework to forecast Covid-19: an insight to the global pandemic.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2021
    Article
  19. Article
  20. 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 2 institutions in 1 country.

Yeisson GutiérrezInstitute of Landscape Ecology University of Münster Münster Germany.ORCID 0000-0002-0166-2933
David OttInstitute of Landscape Ecology University of Münster Münster Germany.
Mareike TöpperwienInstitute for X-Ray Physics University of Göttingen Göttingen Germany.
Tim SaldittInstitute for X-Ray Physics University of Göttingen Göttingen Germany.
Christoph ScherberInstitute of Landscape Ecology University of Münster Münster Germany.ORCID 0000-0001-7924-8911
University of Münster · DEUniversity of Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging techniques are a cornerstone of contemporary biology. Over the last decades, advances in microscale imaging techniques have allowed fascinating new insights into cell and tissue morphology and internal anatomy of organisms across kingdoms. However, most studies so far provided snapshots of given reference taxa, describing organs and tissues under "idealized" conditions. Surprisingly, there is an almost complete lack of studies investigating how an organism's internal morphology changes in response to environmental drivers. Consequently, ecology as a scientific discipline has so far almost neglected the possibilities arising from modern microscale imaging techniques. Here, we provide an overview of recent developments of X-ray computed tomography as an affordable, simple method of high spatial resolution, allowing insights into three-dimensional anatomy both

Indexed as

anatomyanimal imagingcomputed tomographyinternal morphologyμ‐CT

Identifiers

PMID30151184
PMCPMC6106166
OpenAlexW2826692862

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.