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Record W2055394340 · doi:10.3161/150811010x504653

Postnatal Growth and Age Estimation in the Ashy Leaf-Nosed Bat,<i>Hipposideros cineraceus</i>

2010· article· en· W2055394340 on OpenAlexaff
Longru Jin, Aiqing Lin, Keping Sun, Ying Liu, Jiang Feng

Bibliographic record

VenueActa Chiropterologica · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsScience North
Fundersnot available
KeywordsGompertz functionForearmGrowth rateAnatomyMathematicsBiologyStatisticsGeometry

Abstract

fetched live from OpenAlex

We quantified changes in body mass, forearm length, and the total length of the epiphyseal gap of the fourth metacarpal-phalangeal joint of the ashy leaf-nosed bat (Hipposideros cineraceus) based on mark-recapture data obtained in Fangkong Cave in Hekou, Yunnan Province, China. We used these data to develop empirical growth curves, to derive growth rates, to establish age-predictive equations, and to compare growth parameters based on three nonlinear growth models. Forearm length and body mass of pups followed a linear pattern of growth until day 17, with mean growth rates of 0.81 mm/day and 0.09 g/day, respectively and thereafter their growth rates increased more slowly. The length of the epiphyseal gap initially increased linearly up to day 13 and then decreased linearly at a mean rate of 0.07 mm/day until day 37. An equation for estimating age based on forearm length was valid when this dimension was ≤ 27.6 mm, whereas the equation based on the length of the epiphyseal gap was valid for forearm lengths ≥ 24.3 mm. Together, these two equations permit estimation of the age H. cineraceus pups between 1 and 37 days. Of the three nonlinear growth models (logistic, Gompertz, and von Bertalanffy), the logistic equation provided the best fit to the empirical curves for body mass and forearm length.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.296

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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