Characterization of Aoudad and desert bighorn sheep microbiomes in association to disease risk
Bibliographic record
Abstract
Bighorn sheep (Ovis canadensis) inhabit the western United States, northwestern \nMexico, and some of southwestern British Columbia and Alberta. Many herds have \nencountered die-off events thought to be caused by a group of bacterial species \nreferred to as the pneumonia complex, and this complex has been identified as \ntransmissible to bighorn sheep from domestic sheep (Ovis aries) and goats (Capra \nhircus). It is also hypothesized that transmission may occur from Aoudad \n(Ammotragus lervia), an invasive species to Texas that occupies the same habitat as \ndesert bighorn sheep (Ovis canadensis nelsoni) and is in the same subfamily \n(Caprinae). Microbiome dispersal is known to occur in other species through social \nbehavior and shared resources. However, respiratory microbiomes in healthy bighorn \nsheep and aoudad are poorly known but characterizing healthy microbiome \ncomposition is important to understanding transmission as well as the baseline from \nwhich diseased state microbiomes depart. For example, some members of the \npneumonia complex are often found in healthy bighorn sheep, but how their presence \ninfluences overall community structure is unknown. In this study, aoudad and bighorn \nsheep were identified carrying 243 bacterial species in nasal cavities in common and \n202 bacterial species in throat cavities in common. Bacteria associated with the \npneumonia complex were identified in both aoudad and bighorn sheep nasal and throat \nswabs. Nasal microbiomes between aoudad and bighorn sheep are more similar than \nnasal and throat microbiomes within the same animal species. Throat microbiomes \nfollow a similar pattern between species. Spatial-temporal variation between bighorn \nsheep nasal microbiomes was significantly explained between mountain ranges and \ncapture years. The discovery of Mycoplasma ovipneumoniae hosted in aoudad throat \ncavities was also included in this study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".