Description of the Northern Green Anaconda (Eunectes akayima sp. nov. Serpentes; Boidae): What Is in a Name?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".