Running overnight and struggling to find sea ice: long-distance movement by an Arctic fox (<i>Vulpes lagopus</i>) from Russia
Bibliographic record
Abstract
Given the scale, speed, and complexity of recent changes in the Arctic, our understanding of their multiple implications for Arctic biota is still limited. We detail for the first time in the vast Russian Arctic the long-distance movement of an Arctic fox ( Vulpes lagopus (Linnaeus, 1758)) tracked with a GPS/iridium collar providing considerably high precision (several meters) and frequency of locations (every 4 h). Revealed diurnal activity patterns of the Arctic fox indicate that it ran greater distances in night hours and shortest in day hours during the most intense movement period. The movement records suggested several attempts to leave the land, as it seemed to encounter open water four times on different parts of Yamal peninsula. The Arctic fox crossed the Ob Bay towards the Gydan peninsula and satellite imagery of discontinuous ice during crossing suggested that it might have stayed on pieces of floating ice. Our observation may support evidence that a reduction in the duration and extent of sea ice could affect the ability of Arctic foxes to cover long distances and thus, in the long term, the connectivity between populations. Similar studies are needed aiming to understand movement ecology of the Arctic foxes in the changing Arctic.
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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) | 0.001 | 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".