Successful rehabilitation and release of two severely injured Formosan black bears (Ursus thibetanus formosanus) with desensitization to routine treatment procedures
Bibliographic record
Abstract
BACKGROUND: Wildlife rehabilitation is crucial for the recovery of injured endangered species; however, this process can induce significant stress, potentially leading to secondary injuries and complications. This case report details the rehabilitation of two severely injured Formosan black bears (Ursus thibetanus formosanus) with desensitization techniques as an alternative approach to reducing stress while promoting voluntary cooperation during treatment. CASE PRESENTATION: Patient 1 was an adult female bear with injuries, including the loss of the second, third and fourth phalanges of the left forelimb and extensive necrosis of the right palm. Patient 2 was a subadult male suffering from multiple gunshot wounds, severe necrosis of the distal part of the right wrist, and a fracture of the right mandibular ramus and left humerus. Both bears underwent desensitization training, which fostered calmness during routine procedures and facilitated smooth recovery throughout rehabilitation. Pre-release training focused on rebuilding physical capacity and developing natural behaviors, as well as human avoidance, to increase survival and reduce human-bear conflicts. CONCLUSIONS: The successful outcomes, characterized by complete recovery and avoidance of human interactions, underscore the effectiveness of desensitization strategies in wildlife rehabilitation. This approach not only enhances the quality of medical care but also mitigates the risks of post-release conflicts, contributing to the conservation of endangered species.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".