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Record W2006115864 · doi:10.1139/z00-220

Response of American kestrels and gray-tailed voles to vegetation height and supplemental perches

2001· article· en· W2006115864 on OpenAlexvenueno aff
Lisa M. Sheffield, Jamie R. Crait, W. Daniel Edge, Guiming Wang

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersU.S. Environmental Protection Agency
KeywordsPerchVoleMicrotusPredationBiologyVegetation (pathology)Sigmodon hispidusEcologyPopulationFisheryFish <Actinopterygii>Demography

Abstract

fetched live from OpenAlex

We tested the behavioral and demographic responses of American kestrels, Falco sparverius, and gray-tailed voles, Microtus canicaudus, to vegetation height and addition of perches. We conducted our experiment in sixteen 0.2-ha rodent enclosures with four replicates assigned to each of the following treatments: tall vegetation without perches, tall vegetation with perches, short vegetation without perches, and short vegetation with perches. The enclosures were stocked with 20 gray-tailed voles in early November 1998. Before perches were erected during the 12th week of the experiment, kestrels showed a preference for short-vegetation enclosures (P &lt; 0.05). After perches were erected, kestrels used enclosures with perches, showing the greatest preference for short-vegetation enclosures with a perch. Vole populations and recruitment rates were higher in tall-vegetation enclosures than in short-vegetation enclosures, but supplemental perches did not affect vole populations or recruitment. In many agricultural areas where perches are not available, providing supplemental perches may increase accessibility to prey species that cause crop damage. Facilitating predation by raptors may reduce vole populations and reduce the need to use potentially harmful chemicals in pest population management.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.850

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 studies0.0000.001
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations77
Published2001
Admission routes1
Has abstractyes

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