Culling as an Exploratory Field Technique to Reduce Overall Mortality During a Pasturella Spp. Outbreak in a Montana Bighorn Sheep Population
Bibliographic record
Abstract
Several herds of Rocky Mountain bighorn sheep (Ovis Canadensis) in the United States and Canada have experienced all-age die-offs during outbreaks of Pasturella spp. Induced pneumonia. Isolating triggers and remedies for these die-offs remains elusive. Montana Fish, Wildlife and Parks used the statewide Draft Sheep Conservation Strategy as a guide in establishing a field culling-mobile laboratory-media response to a pneumonia/complex outbreak in the East Fork Bitterroot bighorn sheep herd. Montana Fish, Wildlife and Parks employees along with volunteers from the Ravalli County Fish and Wildlife Association, Wild Sheep Foundation and the USDA Forest Service culled 76 sheep from a herd numbering at least 187 animals according to spring 2009 aerial observations. Field personnel discovered six recent bighorn sheep carcasses when culling efforts began in late November. Field personnel discovered one additional bighorn carcass during the three-month culling process. Lab experts conducting onsite necropsies observed evidence of infection in 73 (96%) of the culled sheep. State biologists observed 93 bighorns on this winter range during a cursory aerial survey conducted on 28 December 2009. Preliminary observations from comparing results of sheep selected for culling to field necropsies suggest field personnel detect infected sheep with a high degree of accuracy. We suggest that this technique prevented additional mortalities directly related to pneumonia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".