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Record W4400768513 · doi:10.3390/d16070418

Description of the Northern Green Anaconda (Eunectes akayima sp. nov. Serpentes; Boidae): What Is in a Name?

2024· article· en· W4400768513 on OpenAlexaff
Jesús A. Rivas, Juliana S. Terra, Marijn Roosen, Patrick Champagne, Renata Leite Pitman, Paola De la Quintana, Marco Mancuso, Luis F. Pacheco, Gordon M. Burghardt, Freek J. Vonk, Juan E. García-Pérez, Bryan G. Fry, Sarah Corey-Rivas

Bibliographic record

VenueDiversity · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsAcadia University
Fundersnot available
KeywordsInternational Code of Zoological NomenclatureBiologyZoologyIndigenousEvolutionary biologyNomenclatureEcologyMitochondrial DNAGeographyTaxonomy (biology)

Abstract

fetched live from OpenAlex

While elucidating the evolutionary trajectory of green anacondas, we previously documented the existence of two distinct species, Eunectes akayima sp. nov. and Eunectes murinus (Linnaeus, 1758), that separated approximately 10 million years ago. Our research integrates a novel molecular clock approach, focuses on tectonic plate movements with fossil records as minimal chronological markers, and offers a refined understanding of speciation events in relation to major biogeographical occurrences in South America. Mitochondrial DNA analysis demonstrates a significant genetic divergence between the species, which is supported by a notable difference in sexual size dimorphism (SSD) intensity between the two species, along with other morphological differences. This paper also rectifies earlier oversights in the description of the new species and clarifies taxonomic ambiguities in compliance with the International Code of Zoological Nomenclature (henceforth ICZN). In addition, we designate a neotype for E. murinus to stabilize the group. In an effort to honor Indigenous nations, E. akayima sp. nov. derives its name from the Carib language, advocating for the inclusion of traditional names in scientific discourse. Our paper not only contributes to the taxonomic stability of anacondas but also advocates for the usage of Indigenous names in zoological nomenclature by adopting a more inclusive and flexible approach to the ICZN and eliminating unintended exclusionary practices that we have inherited in science as in other disciplines.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.197
Teacher spread0.184 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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