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POST-NATAL GROWTH AND BREEDING BIOLOGY OF THE HOARY BAT (<i>LASIURUS CINEREUS</i>)

2000· article· en· W2177939086 on OpenAlexaff
Catherine E. Koehler, Robert M. R. Barclay

Bibliographic record

VenueJournal of Mammalogy · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiologyBreedTemperate climateFledgeSeasonal breederForageZoologyEcologyReproductionAnimal sciencePredation

Abstract

fetched live from OpenAlex

Little information is available on growth rates and reproductive effort in microchiropteran bats that breed in temperate areas, are not colonial, and do not hibernate. We measured growth in individual young of the hoary bat, Lasiurus cinereus, a solitary, foliage-roosting, migratory species, and assessed growth rate using changes in forearm length. We tested the prediction that growth is slower in this than in other species because of the less stable thermal environment that adults and juveniles experience. Forearm length and mass of 1-day-old young (X̄ ± SE) were 19.11 ± 0.30 mm and 4.73 ± 0.20 g, respectively. Over 3 years, growth rate of young differed, with young growing slowest (1.14 mm/day) during the coldest year and fastest (1.45 mm/day) during the warmest year. Young were not weaned until 7 weeks of age and nearly 3 weeks after fledging and continued to gain mass over winter. Unlike other species, lactating females did not lose mass through the breeding season. Based on a Levenberg-Marquardt algorithm for nonlinear regression, the growth constant of young hoary bats (0.083 in females) is less than that documented for most other species breeding in temperate North America. Migratory habits of L. cinereus allow adults and young of the year to forage throughout winter and may be associated with slow growth in this species and production of relatively large litters in species of Lasiurus in general.

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 score0.496
Threshold uncertainty score0.442

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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

Citations51
Published2000
Admission routes1
Has abstractyes

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