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Record W3116093016 · doi:10.1139/cjz-2020-0160

Consumption of spiders by the little brown bat (<i>Myotis lucifugus</i>) and the long-eared myotis (<i>Myotis evotis</i>) in the Rocky Mountains of Alberta, Canada

2020· article· en· W3116093016 on OpenAlexaffvenueabout
Dominique G. Maucieri, Robert M. R. Barclay

Bibliographic record

VenueCanadian Journal of Zoology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMyotis lucifugusInsectivoreForagingBiologyCobbleEcologyAbundance (ecology)Competition (biology)PredationHabitat

Abstract

fetched live from OpenAlex

Intraspecific variation in diet and (or) foraging behaviour is one way in which species are able to occupy wide geographical areas with variable environments. The little brown bat (Myotis lucifugus (Le Conte, 1831)), a primarily aerial insectivorous bat, consumes spiders in low temperatures at the start and end of summer in Northwest Territories, Canada, but it consumes spiders all summer, even during high aerial insect abundance, in Alaska, USA. There are no competitors of M. lucifugus in Alaska, but there are in Northwest Territories, suggesting that aerial insect abundance and competition from gleaning bats influences when M. lucifugus consumes spiders. In the Kananaskis area of the Rocky Mountains of Alberta, Canada, we investigated spider consumption by M. lucifugus and the long-eared myotis (Myotis evotis (H. Allen, 1864)), a species more adept at gleaning, to better understand when bats consume spiders. Fecal sample analysis indicated that M. evotis consumed spiders all season long, with greater consumption when the bats were caught near water. Myotis lucifugus did not consume spiders at all. This suggests that M. lucifugus opportunistically consumes spiders when encountered, but does not encounter them in Kananaskis where it forages primarily over open water, unlike in Northwest Territories where it forages in the interior of forests and may encounter spiders more frequently.

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)0.000
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 score0.012
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.012
GPT teacher head0.182
Teacher spread0.169 · 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

Citations13
Published2020
Admission routes3
Has abstractyes

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