Jaguar’s Predation and Human Shield, a Tapir Story
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the risks associated, some species choose to shield behind a predator to decrease predation risk by another predator. In this study, we demonstrate how Baird’s tapirs (Tapirus bairdii) use humans as a “shield” to reduce the risk of being preyed upon by jaguars (Panthera onca). We collected georeferenced photographic records of 23 tapirs (seven of them injured) sighted near human settlements (0 to 5 km) in the Calakmul region of Mexico from 2008 to 2019. Using multidimensional scale analysis, we determined which possible factors (tapir health status, injuries, distance to the settlement, as well as seasonality) are related to the decision of tapirs to approach human settlements. To support our claims of jaguars’ attacks, we described the pattern of injuries believed to have been inflicted by jaguars on tapirs, and we analysed photographs and videos of species of the genus Panthera attacking larger prey than themselves to establish a pattern of injuries and compare it to the injuries observed on tapirs. Our study shows that tapir sightings near human settlements are related to health deterioration, injuries by jaguars and seasonality. The injuries found on tapirs are similar to those caused by other big cats on large prey, providing strong support for jaguar-inflicted wounds. Further studies should investigate whether the increasing human presence in different habitats in the Neotropical region could be influencing the behaviour and distribution of prey and predators.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it