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Record W2028639265 · doi:10.1139/z08-128

Determinants of seasonal variation in activity patterns of mouflon

2008· article· en· W2028639265 on OpenAlexvenueno aff
Gilles Bourgoin, Mathieu Garel, Bram Van Moorter, Dominique Dubray, D. Maillard, Elsa Marty, Jean‐Michel Gaillard

Bibliographic record

VenueCanadian Journal of Zoology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsOvisBiologyReproductionSeasonalityEcologyHerbivore

Abstract

fetched live from OpenAlex

Balancing energetic requirements is a complex process governed by the current condition of the animal, its physiological state, and by the local environment. In response to these factors, animals are expected to adapt their activity patterns. Based on continuous monitoring of 14 GPS-collared animals in southern France, we studied how environmental conditions and reproductive life-cycle periods shape the monthly activity patterns of free-ranging female mouflon ( Ovis gmelini musimon × Ovis sp. (Blyth, 1841)). More specifically, we analyzed total daily activity, diurnal activity, length of activity bouts, and number of activity bouts. We performed multivariate analyses to account for the relationship between several intercorrelated explanatory variables and monthly activity variables. Mouflon decreased their daily activity, diurnal activity, and length of activity bouts during the hot summer months. Such changes might allow animals to reduce thermoregulation costs. The resulting higher activity in winter compared with summer indicates that summer is the most limiting period for large herbivores in Mediterranean area. Both the number of active bouts and the daily activity increased during spring, when females have access to increased food quality, which ensures a faster digestion, and when they may face high energetic requirements owing to reproduction.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.209
Teacher spread0.197 · 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

Citations35
Published2008
Admission routes1
Has abstractyes

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