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Record W2953258592 · doi:10.1111/ele.13230

Indirect effects on fitness between individuals that have never met via an extended phenotype

2019· letter· en· W2953258592 on OpenAlexafffund
David N. Fisher, Jessica A. Haines, Stan Boutin, Ben Dantzer, Jeffrey E. Lane, David W. Coltman, Andrew G. McAdam

Bibliographic record

VenueEcology Letters · 2019
Typeletter
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsMacEwan UniversityMcMaster UniversityUniversity of SaskatchewanUniversity of AlbertaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsHoarding (animal behavior)TerritorialityBiologyEcologyPopulationBreedDemographyKin selectionForaging

Abstract

fetched live from OpenAlex

Interactions between organisms are ubiquitous and have important consequences for phenotypes and fitness. Individuals can even influence those they never meet, if they have extended phenotypes that alter the environments others experience. North American red squirrels (Tamiasciurus hudsonicus) guard food hoards, an extended phenotype that typically outlives the individual and is usually subsequently acquired by non-relatives. Hoarding by previous owners can, therefore, influence subsequent owners. We found that red squirrels breed earlier and had higher lifetime fitness if the previous hoard owner was a male. This was driven by hoarding behaviour, as males and mid-aged squirrels had the largest hoards, and these effects persisted across owners, such that if the previous owner was male or died in mid-age, subsequent occupants had larger hoards. Individuals can, therefore, influence each other's resource-dependent traits and fitness without ever meeting, such that the past can influence contemporary population dynamics through extended phenotypes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0100.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.256
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations31
Published2019
Admission routes2
Has abstractyes

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