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Record W2992558011 · doi:10.1163/1568539x-00003582

Howling by the river: howler monkey (Alouatta palliata) communication in an anthropogenically-altered riparian forest in Costa Rica

2019· article· en· W2992558011 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehaviour · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of CalgaryUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsRiparian zoneRiparian forestGeographyEcologyHabitatVegetation (pathology)ForestryBiology

Abstract

fetched live from OpenAlex

Abstract The ways that forest edges may affect animal vocalization behaviour are poorly understood. We investigated the effects of various types of edge habitat on the loud calls (howls) of a folivorous-frugivorous primate species, Alouatta palliata , with reference to the ecological resource defence hypothesis, which predicts that males howl to defend vegetation resources. We tested this hypothesis across four forest zones — interior, riparian, anthropogenic, and combined forest edges — in a riparian forest fragment in Costa Rica. We predicted vegetation and howling would differ between forest zones, with riparian and interior zones showing the highest values and anthropogenic edge the lowest. Our results indicated that vegetation was richer and howling longer in riparian and interior zones compared to combined and anthropogenic edges, supporting the resource defence hypothesis and providing some of the first evidence in animal communication scholarship for differences in behavioural edge effects between natural riparian and anthropogenic edges.

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.

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 score0.063
Threshold uncertainty score0.587

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 science0.0010.000
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 head0.025
GPT teacher head0.310
Teacher spread0.285 · 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