An Open‐Door Policy: How Removal of a Visual Barrier Improved Welfare in Zoo‐Housed Bald Eagles (<i>Haliaeetus leucocephalus</i>)
Bibliographic record
Abstract
Birds of prey are renowned for their excellent visual acuity, but they are often not given visual access consistent with their natural behavior when housed under managed care. Often, these birds are housed under managed care after sustaining injuries, which prohibits their return to the wild. In addition, many of these rescued raptors do not have the same history of acclimation to human presence as other zoo animals due to being wild-hatched. These factors lead to a potential welfare concern for raptors under managed care, which may not appropriately address their natural and individual histories. We assessed how the removal of a visual barrier (two large doors) may have affected behavior and space use of two bald eagles (Haliaeetus leucocephalus) housed at Zoo Miami. Before the visual barrier being removed, the eagles could not see people approaching their habitat from one out of two possible sides. We found that for one individual, stress behaviors such as gular fluttering significantly decreased after the removal of the visual barrier, and resting significantly increased. The birds also utilized their habitat more evenly after the visual barrier was removed and were seen at higher, more species-typical altitudes within the habitat. These findings suggest that increased environmental visual access for zoo-housed raptors may be a simple way to improve their overall welfare.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".