Dall’s sheep survey within Yukon-Charley Rivers National Preserve: July 2023
Bibliographic record
Abstract
A minimum count survey of Dall’s sheep (Ovis dalli) in Yukon-Charley Rivers National Preserve was conducted from July 18 to 20, 2023. The Preserve was last surveyed in July of 2018. The current survey examined the same 7 core survey units as the previous survey and the Ogilvie Mountains. In the core area (the 7 units most often surveyed), 70 sheep (32 ewes, 13 lambs, 6 yearlings and 19 rams) were detected. This constitutes a 75% decrease from the long-term average (284 sheep, 1997–2018) and a 68% decrease from the last survey (221 sheep, 2018). There were 40 lambs, 19 yearlings, and 59 rams per 100 ewes in the core area. Declines varied by space and sex classes. Declines were greater in survey units with historically fewer sheep and lower proportions of ewes (91% decline; 5580 Mountain, Copper Mountain, Diamond Fork, Twin Mountain) versus the survey units with more sheep and higher proportions of ewes (67% decline; Charley River, Cirque Lakes, Mount Sorenson). Across the latter more populous survey units, ewes and rams declined by 70% and 40%, respectively, compared to the long-term average. For the first time, no sheep were observed in two of the survey units (Copper Mountain and Diamond Fork). In the Ogilvie Mountains, 26 sheep were detected (18 ewes, 4 lambs, 0 yearling and 4 rams) representing a 28% decline since the last survey. This translates to 22 lambs, 0 yearlings and 22 rams per 100 ewes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".