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Record W3166255061 · doi:10.1139/cjz-2020-0177

Cathemeral activity by brown-throated three-toed sloths (<i>Bradypus variegatus</i>) in central Amazonian flooded igapó forests

2021· article· en· W3166255061 on OpenAlexvenueno aff
Matheus J. Castro-Sa, Renann H.P. Dias-Silva, Adrian A. Barnett

Bibliographic record

VenueCanadian Journal of Zoology · 2021
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsnot available
FundersInstituto Nacional de Pesquisas da AmazôniaConselho Nacional de Desenvolvimento Científico e TecnológicoIdea Wild
KeywordsBiologyAbiotic componentAmazonianEcologySlothHabitatAmazon rainforest

Abstract

fetched live from OpenAlex

Both biotic and abiotic factors are important for maintaining the activity cycles of animals and may determine the most advantageous periods for eating, moving, and sleeping. Although the solar day–night cycle is among the most central of abiotic variables, a number of species are active both day and night. Three-toed sloth (genus Bradypus Linnaeus, 1758) populations across the Neotropics show this pattern, with activity occurring at various times within the 24 h cycle. In the current study, we used radio-tracking techniques to investigate the daily temporal patterning of brown-throated three-toed sloth (Bradypus variegatus Schinz, 1825) displacement in Amazonian flooded igapó forest and compared the results with populations studied in other habitats. We concluded that igapó sloths are cathemeral, and discussed that environmental temperature, nutritional needs and the presence of predators may be the main factors influencing their activity pattern.

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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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