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Record W2808194670 · doi:10.11646/zootaxa.4433.3.4

Rove beetles collected with carrion traps (Coleoptera: Staphylinidae) in Quercus forest of Cerro de García, Jalisco and Quercus, Quercus-pine, and pine forests in other jurisdictions of Mexico

2018· article· en· W2808194670 on OpenAlexaff
William Rodríguez, José Luís Navarrete-Heredia, Jan Klimaszewski

Bibliographic record

VenueZootaxa · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsCarrionBiologyEcologyHabitatForestryGeography

Abstract

fetched live from OpenAlex

We present the species diversity of rove beetles (Coleoptera: Staphylinidae) collected with carrion baited traps in Quercus forests of Cerro de García, Jalisco, and provide a compilation of published species records in Quercus, Quercus-pine and pine forests in other jurisdictions of Mexico. This work includes taxonomic notes, information on species phenology, distribution, and their occurrence in Cerro de García (if applicable), and other jurisdictions of Mexico. In Cerro de García, 75 species were collected in total, of which 16 are shared with other Quercus forests in different locations, and 9 species are provided with new habitat data. The remaining individuals were only determined to morphospecies. In Mexico, there are 77 known species of rove beetles collected with carrion traps (determined to species or near species) and recorded from Quercus, Quercus-pine and pine forests. These species belong to 30 genera, 11 tribes and 10 subfamilies. This study provides biological information on Mexican rove beetles captured with carrion traps and highlights the importance of rove beetles as indicator species of habitat change for conservation analysis, forestry, agronomy and forensic sciences studies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.977

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 studies0.0000.001
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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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 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

Citations6
Published2018
Admission routes1
Has abstractyes

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