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Record W2099592558 · doi:10.3356/jrr-07-30.1

Natural History of the Threatened Bearded Screech-Owl (Megascops Barbarus) in Chiapas, Mexico

2008· article· en· W2099592558 on OpenAlexaff
Paula L. Enríquez, Kimberly M. Cheng

Bibliographic record

VenueJournal of Raptor Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyDry seasonInsectivoreEvergreenEcologyThreatened speciesTytoZoologyEndangered speciesNest (protein structural motif)PredationHabitat

Abstract

fetched live from OpenAlex

We describe morphological measurements, breeding biology, roost-site characteristics, and diet of the endemic and threatened Bearded Screech-Owl (Megascops barbarus) in the central highlands of Chiapas, Mexico. The first nest recorded for this species was in a natural cavity of an old oak (Quercus laurina) and contained a single nestling. Four roosting sites were located, two in Clethra chiapensis (evergreen broadleaf) and two in Pinus ayacahuite (pine; mean height = 3.4 m). Fecal analysis indicated that diet was primarily insectivorous, consisting of Melononthidae (Coleoptera; 72.3%), along with a few Orthoptera (9.2%), Lepidoptera (3.1%), and Arachnida (1.5%). Data from 39 owls (24 captured and 15 skins) were used for morphology analysis. This species exhibited reversed sexual dimorphism, with females having greater mass and longer tails than males. Molting occurred during the rainy season (July to October), with the primary and secondary feathers being molted simultaneously. Subcutaneous fat was moderate to abundant in the dry season only (December to May). Maximum longevity we recorded was at least 4.17 yr. These first natural history data for the species provides preliminary information for understanding the ecological requirements of the Bearded Screech-Owl in fragmented tropical montane forest.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.057
GPT teacher head0.304
Teacher spread0.247 · 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.

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

Citations9
Published2008
Admission routes1
Has abstractyes

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