MétaCan
Menu
Back to cohort
Record W2138995676 · doi:10.1898/13-02.1

Roost-Site Selection and Movements of Little Brown Myotis (<i>Myotis lucifugus</i>) in Southwestern Yukon

2014· article· en· W2138995676 on OpenAlexafffundabout
Lea A. Randall, Thomas S. Jung, Robert M. R. Barclay

Bibliographic record

VenueNorthwestern Naturalist · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsYukon Department of EnvironmentUniversity of Calgary
FundersAssociation of Canadian Universities for Northern StudiesNatural Sciences and Engineering Research Council of CanadaNorthwestern UniversityArctic Institute of North America
KeywordsMyotis lucifugusForagingSnagEcologyBorealGeographyTaigaHome rangeHabitatBiology

Abstract

fetched live from OpenAlex

Diurnal roost sites are a critical resource for bats. Despite their importance, we know little about the roosting habits of Little Brown Myotis (Myotis lucifugus) in the boreal forest of northwestern Canada and Alaska. To locate diurnal roost sites and determine minimum distances to foraging areas, we radio-tagged 10 Little Brown Myotis (7 adult females, 3 adult males) in the boreal forest of southwestern Yukon, Canada. All of the females roosted in a single building, with 1 using a bat house for 2 nights. In contrast, the males used a variety of roost sites, including buildings, rock cliffs, and trees, and switched roosts periodically. We observed sex-biased movements, with adult males traveling a significantly shorter distance between their diurnal roost sites and a key foraging area than adult females. Males tended to roost near a key foraging area, whereas radio-tagged females flew >5 km from their diurnal roosts to forage. Our data are some of the first obtained via radio-telemetry for Little Brown Myotis in the boreal forest and confirm that the roosting behavior of the sexes is different. That all of the radio-tagged females primarily used 1 roost site in town and flew relatively far to a key foraging area suggests that these critical resources may be somewhat limiting in our study area.

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 score0.208
Threshold uncertainty score0.801

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations32
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueNorthwestern NaturalistSame topicBat Biology and Ecology StudiesFrench-language works237,207