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Record W2085814789 · doi:10.1242/jeb.062034

Interplay between plasma oxidative status, cortisol and coping styles in wild alpine marmots, <i>Marmota marmota</i>

2011· article· en· W2085814789 on OpenAlexaff
David Costantini, Caterina Ferrari, Cristian Pasquaretta, Elena Cavallone, Claudio Carere, Achaz von Hardenberg, Denis Réale

Bibliographic record

VenueJournal of Experimental Biology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Environment Research CouncilSight Research UK
KeywordsCoping (psychology)StressorOxidative stressPsychologyInternal medicineEndocrinologyBiologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Variation in how individuals cope behaviourally and physiologically with stressors is widespread and can have a significant impact on life-history traits and fitness. Individual coping styles are characterised by differential behavioural and adrenocortical reactivity to various challenges. As stress hormones can affect the production of reactive chemical species and the antioxidant status, individuals with different coping styles may differ also in oxidative status. Field studies on wild mammalian populations are few in number and none so far has simultaneously tested the relationship between coping style, adrenocortical reactivity and oxidative status in the same individuals. We measured individual variation in coping styles along a proactive-reactive continuum together with variation in baseline and stress-induced plasma oxidative damage, plasma non-enzymatic antioxidant capacity and cortisol in wild alpine marmots, Marmota marmota. Confirmatory path analysis revealed that different coping styles are accompanied by different baseline and stress-induced plasma oxidative statuses. Our findings also highlight the potential role of cortisol as a mediator of such differences.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.275

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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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 designBench or experimental
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

Citations71
Published2011
Admission routes1
Has abstractyes

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