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INDIVIDUAL AND POPULATION-LEVEL VARIABILITY IN DIETS OF PALLID BATS (<i>ANTROZOUS PALLIDUS</i>)

2001· article· en· W2179246740 on OpenAlexafffund
Dave S. Johnston, M. Brock Fenton

Bibliographic record

VenueJournal of Mammalogy · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsYork University
FundersYork UniversityNatural Sciences and Engineering Research Council of CanadaSan José State University
KeywordsPredationForagingBiologyPopulationCaptivityZoologyEcologyRange (aeronautics)Demography

Abstract

fetched live from OpenAlex

At 2 locations in California (coastal, Tocaloma; desert, Caliente), analysis of feces presented a significantly higher number of prey types for the diets of Antrozous pallidus than analysis of culled parts of prey. Analysis of diet by culled parts was biased toward larger, harder prey, and some softer, smaller prey were missed altogether. Observation of individuals feeding revealed that some bats ate prey without culling any parts, whereas others culled only the hardest and largest parts. Analysis of feces from tagged adult male pallid bats from Tocaloma (1993–1994) and Caliente (1994–1995) suggested that bats were generalists, but whereas diets of individuals at Caliente reflected the average diet for the group, none of the individuals at Tocaloma ate the average diet. Variation in the diets of A. pallidus reflects prey availability and individual foraging behavior. Tocaloma bats did not significantly change their diets throughout summer; Caliente bats did. Bats from Caliente and Tocaloma ate different prey than arthropods caught in pit traps, suggesting that bats in both populations were selective foragers. In captivity, hunting A. pallidus took flying and nonflying prey. Some flying prey were forced against a surface before capture, adding a novel dimension to the range of behavior involved in “gleaning.”

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)0.001
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 score0.020
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.240
Teacher spread0.203 · 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

Citations52
Published2001
Admission routes2
Has abstractyes

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