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Beyond spiders: Harvestmen as predators of anurans in the Neotropics

2025· article· W4416940336 on OpenAlexaff
Esteban Calvache, Osvaldo Villarreal, Cynthia Ávila-Rojas, Alexander Griffin Bentley, Chiara Correa-Zanotti, Maida Gutierrez-Arboleda, Katherine Iñiguez, Juan Carlos Narváez Barandica, Lizardo Proaño, Mateo Reyes-Vizcaino, Luis Fernando García

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsDeer Lodge Centre
Fundersnot available
KeywordsPredationInvertebratePredatorAssemblage (archaeology)Apex predator

Abstract

fetched live from OpenAlex

Arthropods are traditionally viewed as invertebrate prey and predators for vertebrates, a paradigm increasingly challenged, especially among arachnids. While spiders are documented frog predators, the capacity of other groups like harvestmen (Opiliones) has remained anecdotal. We report novel field observations of anuran predation by multiple Cranaidae harvestmen species across Neotropical localities. These records include active capture and consumption of live frogs, demonstrating their role as opportunistic mesopredators. Alongside new spider predation records, our findings substantially advance Opiliones ecology by confirming vertebrate predation occurs in multiple, disjunct species. This reveals vertebrate consumption among arachnids is more taxonomically widespread than recognized, underscoring the need to include Opiliones as potential predators in Neotropical trophic models.

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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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