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Record W4411317219 · doi:10.1515/mammalia-2025-0019

Porcupine (<i>Coendou</i> spp.) geophagy in an Amazonian landscape of fear

2025· article· en· W4411317219 on OpenAlexaff
Sam Pottie, Erin Marcela Rivera Groves, Andrew Whitworth, Christopher Beirne, Raul Bello, Adrián Forsyth

Bibliographic record

VenueMammalia · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAmazonianPorcupineGeographyZoologyEcologyBiologyAmazon rainforest

Abstract

fetched live from OpenAlex

Abstract Neotropical porcupines ( Coendou spp.) remain poorly studied, with much of our knowledge derived from anecdotal observations or research on captive individuals. In this study, we used camera traps across multiple survey designs – an arboreal grid, a terrestrial grid, and at mineral licks – to investigate habitat use and geophagy in sympatric porcupine species in southeastern Peru. We obtained a total survey effort of 70,863 trap-nights, during which we collected 1,956 camera-trap photos and videos belonging to 526 independent events of Coendou bicolor , Coendou longicaudatus , and Coendou ichillus . Our results provide a detailed account of geophagy in C. bicolor and C. longicaudatus . We also used relative abundance indices (RAIs) to assess habitat use in these species with results showing a relatively high RAI for C. ichillus in the canopy (35.56 independent events per 1,000 trap-nights), as well as for C. bicolor and C. longicaudatus at mineral licks on ground level (97.82 and 41.16, respectively). By identifying these habitat preferences through camera trap data, we provide key insights for future research, while also expanding our knowledge on the ecology of these elusive species.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.435

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 head0.011
GPT teacher head0.326
Teacher spread0.315 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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