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Losing out to improve group fitness

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 17 Dec 2021Embargo end date: 17 Dec 2021 Switzerland English Publisher:eLife Sciences Publications, LtdJournal:eLife, volume 10 (eissn: 2050-084X, Copyright policy )
Authors: Kramer, Jos; Kümmerli, Rolf;

doi: 10.7554/elife.75243 , 10.5167/uzh-220099

pmid: 34919055

pmc: PMC8683077

Losing out to improve group fitness

Abstract

A mathematical model provides clues as to why members of a group divide tasks between them even when specialisation reduces the performance of individuals.

Country
Switzerland
Related Organizations
Keywords

division of labor, Evolutionary Biology, General Immunology and Microbiology, QH301-705.5, General Neuroscience, Science, Q, R, 2800 General Neuroscience, specialisation, synergy, cooperation, 610 Medicine & health, Genetics and Molecular Biology, General Medicine, 1300 General Biochemistry, Genetics and Molecular Biology, 2400 General Immunology and Microbiology, General Biochemistry, Medicine, Humans, Biology (General), 11493 Department of Quantitative Biomedicine, Exercise

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold
Related to Research communities
Neuroscience