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Record W2114238013 · doi:10.1898/13-30.1

Bat Activity and Use of Hibernacula in Wood Buffalo National Park, Alberta

2014· article· en· W2114238013 on OpenAlexafffundabout
Jesika P. Reimer, Cori L. Lausen, Robert M. R. Barclay, Sharon Irwin, Mike K Vassal

Bibliographic record

VenueNorthwestern Naturalist · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsWildlife Conservation Society CanadaParks CanadaUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaParks CanadaAlberta Conservation AssociationBat Conservation International
KeywordsMyotis lucifugusEptesicus fuscusHuman echolocationCaveNational parkEcologyHibernation (computing)GeographyBiologyHabitat

Abstract

fetched live from OpenAlex

Relatively little is known about bats or bat hibernacula in northern Canada. We were interested in documenting species diversity and seasonal activity of bats in Wood Buffalo National Park, including use of a cave hibernaculum by Little Brown Myotis (Myotis lucifugus), Northern Myotis (Myotis septentrionalis), and Big Brown Bats (Eptesicus fuscus). We used acoustic monitoring and mist netting over 3 y to assess species diversity and seasonal activity. We also recorded cave temperature during hibernation. During the summers of 2010 to 2012, we captured 470 bats including M. lucifugus, M. septentrionalis, and E. fuscus. We identified 2 migratory species via echolocation recordings in 2011: Lasiurus cinereus (Hoary Bat) was recorded in the area from mid-May to early October, and Lasiurus borealis (Eastern Red Bat) from mid-June to early August. Resident bat activity at the hibernaculum was greatest from mid-June to early September. Our findings provide a first approximation of species diversity and describe seasonal activity patterns of bats in Wood Buffalo National Park.

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 score0.295
Threshold uncertainty score0.995

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 head0.023
GPT teacher head0.228
Teacher spread0.204 · 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

Citations16
Published2014
Admission routes3
Has abstractyes

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