Waterhole use and diel activity pattern of ocelots in Calakmul rainforest, Mexico
Bibliographic record
Abstract
We aimed to evaluate the temporal and spatial use of waterholes by ocelots in Calakmul Biosphere Reserve (CBR), Mexico. From 2014 to 2017, we monitored 11 waterholes with camera traps. We compared diel activity patterns with circular statistics depending on waterholes’ level of human intensity and distance to the Calakmul road, seasonality, and sex. We identified 40 different ocelots. Four waterholes were the most important ones, being 2 of them close to the road. Individuals took on average 19 days to return to waterholes. The diel activity of ocelots was 63.67% nocturnal, 20.70% crepuscular and 15.60% diurnal, and they were more diurnal in waterholes distant from the road. Their activity pattern was bimodal and it did not change between any of the categories tested. This is the first study to determine the spatial and temporal activity of ocelots in waterholes of Mexico. Ocelots are mainly nocturnal, and this pattern is conserved throughout CBR, however, they are able to adjust slightly their activity depending on extrinsic factors, such as an increased human presence. In the Calakmul region, all waterholes are crucial, and we particularly emphasize the conservation of the most important waterholes for ocelots, especially the ones close to the road.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".