Taxonomy, allometry, sexual dimorphism, and conservation of the trans-Andean watersnake <i>Helicops danieli</i> Amaral, 1937 (Serpentes: Dipsadidae: Hydropsini)
Bibliographic record
Abstract
The extensive lack of knowledge on the morphological aspects of South American watersnakes includes a poor understanding of phenotypic parameters, intraspecific variation, and conservation of the trans-Andean Helicops species, Daniel’s Keelback (Helicops danieli Amaral, 1937). For the first time, we provide a multidisciplinary view using key features (e.g., morphology and niche modeling) to improve the taxonomic recognition of this species, as well as describing ontogenetic color changes, allometry, sexual dimorphism, and the conservation status of this poorly studied snake. First, we emended the morphological diagnosis of H. danieli with 23 characters and detected that juvenile tail length is positively related to allometric growth, and that juveniles differ from adults through the presence of the white nuchal collar. Females are larger than males for snout–vent length, whereas males showed proportionally longer tails and smaller head length growth. Suitable areas for H. danieli are restricted to the trans-Andean regions from the Magdalena drainage to the Caribbean coast, which also showed high values of anthropic impacts. Our multidisciplinary approach provided new insights into this South American watersnake’s morphology, intraspecific variation, and distribution.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".