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Record W2274212296 · doi:10.11646/zootaxa.2626.1.2

New records of araneid spiders (Araneae: Araneidae) in the Colombian Amazon Region

2010· article· en· W2274212296 on OpenAlexaff
Jaime Pinzón, Ligia R. Benavides, Alexander Sabogal

Bibliographic record

VenueZootaxa · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpider Taxonomy and Behavior Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAmazon rainforestBiologyDistribution (mathematics)EcologyGeography

Abstract

fetched live from OpenAlex

We have revised all the specimens of Araneidae from the Colombian Amazon Region in the Arachnological Collection of the Instituto de Ciencias Naturales at the Universidad Nacional de Colombia (ICN), in addition to the specimens collected between 2000 and 2004 by the authors in the lower Caquetá and Apaporis rivers (Amazonas and Vaupés, Colombia). A total of 77 new records for Araneidae in the Colombian Amazon are reported; 26 of these species are new records for the country and the region in addition to 15 more species known for Colombia but newly recorded in the region, the distribution of the remaining 36 species is expanded within the region. The genera Encyosaccus Simon 1865 (E. sexmaculatus Simon 1895), Hingstepeira Levi 1995 (H. folisecens Hingston 1932) and Micrepeira Schenkel 1953 (M. fowleri Levi 1995 and M. tubulofasciens Hingston 1932) are recorded for the first time in Colombia. From this revision, it is evident the great amount of new information available in museum collections. Due to the strategic geographic position of Colombia, species inventories in different localities of the Colombian Amazon Region are important to fill distributional gaps of many species in South America. This work contributes to the knowledge of geographic distribution patterns of orb-weaving species in Colombia and in the entire Amazon Region.

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)0.001
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 score0.067
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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
Published2010
Admission routes1
Has abstractyes

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