Experimental Transmission of Bighorn Sheep Sinus Tumors to Bighorn Sheep ( <i>Ovis canadensis canadensis</i> ) and Domestic Sheep
Bibliographic record
Abstract
Bighorn sheep sinus tumors are a recently described disease affecting the paranasal sinuses of Rocky Mountain bighorn sheep (Ovis canadensis canadensis). Several features of this disease suggest an infectious cause, although a specific etiologic agent has not been identified. To test the hypothesis that bighorn sheep sinus tumors are caused by an infectious agent, we inoculated 4 bighorn sheep lambs and 4 domestic sheep lambs intranasally with a cell-free filtrate derived from a naturally occurring bighorn sheep sinus tumor; we held 1 individual of each species as a control. Within 18 months after inoculation, all 4 inoculated domestic sheep (100%) and 1 of the 4 inoculated bighorn sheep (25%) developed tumors within the ethmoid sinuses or nasal conchae, with features similar to naturally occurring bighorn sheep sinus tumors. Neither of the uninoculated sheep developed tumors. Histologically, the experimentally transmitted tumors were composed of stellate to spindle cells embedded within a myxoid matrix, with marked bone production. Tumor cells stained positively with vimentin, S100, alpha smooth muscle actin, and osteocalcin, suggesting origin from a multipotent mesenchymal cell. A periosteal origin for these tumors is suspected. Immunohistochemical staining for the envelope protein of JSRV (with cross-reactivity to ENTV) was equivocal, and PCR assays specific for these agents were negative.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".