Towards a Better Understanding of the Effects of UV on Atlantic Walruses, Odobenus rosmarus rosmarus: A Study Combining Histological Data with Local Ecological Knowledge
Bibliographic record
Abstract
Walruses, Odobenus rosmarus, play a key role in the Arctic ecosystem, including northern Indigenous communities, which are reliant upon walruses for aspects of their diet and culture. However, walruses face varied environmental threats including rising sea-water temperatures and decreasing ice cover. An underappreciated threat may be the large amount of solar ultraviolet radiation (UV) that continues to reach the Arctic as a result of ozone loss. UV has been shown to negatively affect whales. Like whales, walrus skin is unprotected by fur, but in contrast, walruses spend long periods of time hauled-out on land. In this study, we combined the results of histological analyses of skin sections from five Atlantic walruses, Odobenus rosmarus rosmarus, collected in Nunavik (Northern Quebec, Canada) with qualitative data obtained through the interviews of 33 local walrus hunters and Inuit Elders. Histological analyses allowed us to explore UV-induced cellular lesions and interviews with experienced walrus hunters and Elders helped us to study the incidences and temporal changes of UV-induced gross lesions in walruses. At the microscopic scale, we detected a range of skin abnormalities consistent with UV damage. However, currently such UV effects do not seem to be widely observed at the whole-animal level (i.e., absence of skin blistering, erythema, eye cataract) by individuals interviewed. Although walruses may experience skin damage under normal everyday UV exposure, the long-term data from local walrus hunters and Inuit Elders did not report a relation between the increased sun radiation secondary to ozone loss and walrus health.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".