Back to the wild: Post-translocation GPS monitoring of a rehabilitated ocelot (Leopardus pardalis) in a forest-agriculture matrix in the Osa Peninsula, Costa Rica
Bibliographic record
Abstract
The sparsity of post-translocation monitoring data for rehabilitated felids leaves a pressing gap in our current understanding of their integration into and use of novel landscapes. Remote monitoring tools such as GPS collars can provide crucial insights into animal movement behavior and habitat selection following translocation and assist in the decision-making process for rehabilitation and release sites. In January 2023, a young male ocelot was released on the Osa Peninsula, Costa Rica, after eight months of rehabilitation following a vehicle strike. Six months of post-translocation monitoring using a GPS and VHF-enabled collar revealed distinctive spatial patterns between the ocelot’s initial exploratory phase (~75 days) and subsequent residential period, as well as a selection for agricultural-forest matrix habitat over primary forest. We discuss the findings in terms of learning lessons for future post-release monitoring effects and provide insight into an individual’s patterns of habitat selection in an anthropogenically modified landscape.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".