Prevalence of injuries in a <i>Caiman crocodilus chiapasius</i> (Bocourt 1876) population from the South Pacific coast of Mexico
Bibliographic record
Abstract
Crocodilians injuries are indicators of their health and social interactions. We analyzed the prevalence and distribution of injuries in spectacled caiman (Caiman crocodilus chiapasius) from the Biosphere Reserve of La Encrucijada (BRLE) in relation to the habitat, size, and sex of individuals. We collected data on injuries in caimans captured during nocturnal surveys (2014–2022) in the estuary and swamps of the BRLE. We determined the sex of each caiman, measured their snout–vent length, and registered the type of injury and body region where injuries were detected. From all records, 102 of 301 caimans (33.9%) presented injuries and they were more likely to be injured in the estuary than in the swamps, probably due to the presence of a larger sympatric crocodile species in the estuary (Crocodylus acutus). Sex had no effect on the proportion of injured individuals, but larger caimans have a higher probability of being injured than smaller ones, explained by an ontogenetic change in the individuals’ behaviors. Habitat, sex, and size class of individuals do not influence the number of injuries on different body regions. The tail was the most injured body region (17.6% of individuals), followed by the abdomen (13.0%), back (12.6%), head (9.6%), and extremities (4.0%).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".