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Record W2616091764 · doi:10.1098/rsbl.2017.0175

Cannibalism by damselflies increases with rising temperature

2017· article· en· W2616091764 on OpenAlexafffund
Denon Start, Devin Kirk, Dylan Shea, Benjamin Gilbert

Post-publication record

NatureCorrection
ReasonError in Data;Error in Text;
Date10/6/2021 0:00
Flagged by OpenAlex?No. Retraction Watch records this, and OpenAlex does not flag it.

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueBiology Letters · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntraspecific competitionDamselflyBiologyCannibalismEcologyTrophic levelClimate changeZoologyPredationOdonata

Abstract

fetched live from OpenAlex

Abstract Trophic interactions are likely to change under climate warming. These interactions can be altered directly by changing consumption rates, or indirectly by altering growth rates and size asymmetries among individuals that in turn affect feeding. Understanding these processes is particularly important for intraspecific interactions, as direct and indirect changes may exacerbate antagonistic interactions. We examined the effect of temperature on activity rate, growth and intraspecific size asymmetries, and how these temperature dependencies affected cannibalism in Lestes congener, a damselfly with marked intraspecific variation in size. Temperature increased activity rates and exacerbated differences in body size by increasing growth rates. Increased activity and changes in body size interacted to increase cannibalism at higher temperatures. We argue that our results are likely to be general to species with life-history stages that vary in their temperature dependencies, and that the effects of climate change on communities may depend on the temperature dependencies of intraspecific interactions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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 teacher head, 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

Citations28
Published2017
Admission routes2
Has abstractyes

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