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Energy metabolism and animal personality

2008· article· en· W2115527601 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOikos · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoldnessPersonalityPsychologyVariation (astronomy)Energy metabolismEcologyBiologySocial psychology

Abstract

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In this paper we show how animal personality could explain some of the large inter‐individual variation in resting metabolic rate (MR) and explore methodological and functional linkages between personality and energetics. Personality will introduce variability in resting MR measures because individuals consistently differ in their stress response, exploration or activity levels, all of which influence MR measurements made with respirometry and the doubly‐labelled water technique. Physiologists try to exclude these behavioural influences from resting MR measurements, but animal personality research indicates that these attempts are unlikely to be successful. For example, because reactive animals “freeze” when submitted to a stress, their MR could be classified as “resting” because of immobility when in fact they are highly stressed with an elevated MR. More importantly, recent research demonstrating that behavioural responses to novel and highly artificial stimuli are correlated with both behaviour and fitness under more natural circumstances calls into question the wisdom of excluding these behavioural influences on MR measurements. The reason that intra‐specific variation in resting MR are so weakly correlated with daily energy expenditure (DEE) and fitness, may be that the latter two measures fully incorporate personality while the former partially excludes its influence. Because activity, exploration, boldness and aggressiveness are energetically costly, personality and metabolism should be correlated and physiological constraints may underlie behavioural syndromes. We show how physiological ecologists can better examine behavioural linkages between personality and metabolism, as required to better understand the physiological correlates of personality and the evolutionary consequences of metabolic variability.

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.

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 score0.910
Threshold uncertainty score0.379

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 studies0.0000.000
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 head0.033
GPT teacher head0.224
Teacher spread0.191 · 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