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Record W2053628163 · doi:10.1139/z02-154

Individual and seasonal differences in antipredatory behaviour of root volesa field experiment

2002· article· en· W2053628163 on OpenAlexvenueno aff
Zbigniew Borowski

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWeaselBiologyMicrotusVoleSeasonal breederPredationPredatorEcologyArvicolinaeForagingHunting seasonZoologyPopulationDemography

Abstract

fetched live from OpenAlex

The response of root vole (Microtus oeconomus) to least weasel (Mustela nivalis) odours during breeding (August) and nonbreeding seasons (November) was studied in the root voles' natural habitat. The aim of this study was to determine if antipredator behaviour of the root vole changed between breeding and nonbreeding seasons and if this change was closely related to individual environmental cues, e.g., weasel odours. It was found that when bait and weasel odour was used, trappability was greater in breeding season than in nonbreeding season. Moreover, in the breeding season, heavier (i.e., older) voles were more frequently captured than lighter (i.e., younger) ones. Results show that voles' antipredator behaviour of weasel avoidance changes seasonally and that during the breeding season voles display a trade-off conflict between predator risk and foraging, if predator risk is high. It is possible that older voles are driven to reproduce in the current breeding season and thus display less weasel avoidance than do younger voles, which have higher probability of surviving to the next breeding season. Results indicate that indirect (nonlethal) effects of mammalian predators on voles' behaviour strongly depend on age, sexual activity, and season.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.998

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)0.0030.000

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 head0.024
GPT teacher head0.226
Teacher spread0.202 · 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.

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

Citations26
Published2002
Admission routes1
Has abstractyes

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