Evidence map›Paper›PMID 38261631›Full record

ArticlePLoS biology2024

Recording animal-view videos of the natural world using a novel camera system and software package.

Vera Vasas, Mark C Lowell, Juliana Villa, Quentin D Jamison, Anna G Siegle, Pavan Kumar Reddy Katta, Pushyami Bhagavathula, Peter G Kevan, Drew Fulton, Neil Losin and 5 more

Abstract read
In one paragraph

Article in PLoS biology, 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. Review
  4. 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

15 authors.

Vera VasasSchool of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom.
Mark C LowellTheorem Engine, Alexandria, Virginia, United States of America.
Juliana VillaDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.
Quentin D JamisonDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.
Anna G SiegleDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.
Pavan Kumar Reddy KattaDepartment of Computer Science, George Mason University, Fairfax, Virginia, United States of America.
Pushyami BhagavathulaDepartment of Computer Science, George Mason University, Fairfax, Virginia, United States of America.
Peter G KevanSchool of Environmental Sciences, University of Guelph, Guelph, Canada.
Drew FultonDrew Fulton Photography, Gainesville, Florida, United States of America.
Neil LosinDay's Edge Productions, San Diego, California, United States of America.
David KepplingerDepartment of Statistics, George Mason University, Fairfax, Virginia, United States of America.
Michael K YetzbacherUS Naval Research Laboratory, Washington, DC, United States of America.
Shakiba SalehianDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.
Rebecca E ForknerDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.
Daniel HanleyDepartment of Biology, George Mason University, Fairfax, Virginia, United States of America.

Funding

Blandy Experimental FarmGeorge Mason’s Office of Student Scholarship, Creative Activities, and ResearchNational Geographic SocietyOffice of Research, Innovation, and Economic Impact at George Mason University
6 · The paper itself

Abstract

Plants, animals, and fungi display a rich tapestry of colors. Animals, in particular, use colors in dynamic displays performed in spatially complex environments. Although current approaches for studying colors are objective and repeatable, they miss the temporal variation of color signals entirely. Here, we introduce hardware and software that provide ecologists and filmmakers the ability to accurately record animal-perceived colors in motion. Specifically, our Python codes transform photos or videos into perceivable units (quantum catches) for animals of known photoreceptor sensitivity. The plans and codes necessary for end-users to capture animal-view videos are all open source and publicly available to encourage continual community development. The camera system and the associated software package will allow ecologists to investigate how animals use colors in dynamic behavioral displays, the ways natural illumination alters perceived colors, and other questions that remained unaddressed until now due to a lack of suitable tools. Finally, it provides scientists and filmmakers with a new, empirically grounded approach for depicting the perceptual worlds of nonhuman animals.

Indexed as

LightingSoftwareAnimalsMotion

Identifiers

PMID38261631
PMCPMC10805291

What OpenQuestion holds

Textmetadata
LicenceCC0
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.