Evaluating the utility of harvester-collected samples for muskox (Ovibos moschatus) pregnancy diagnostics
Bibliographic record
Abstract
Monitoring wildlife health in remote and vast regions of the Arctic can be difficult and expensive, but community-based monitoring programs can help alleviate these issues. Reliable bio-monitoring tools, compatible with sample types collected from remote regions, are needed to determine indicators of population health, such as reproductive rates. We sought to establish methods to diagnose pregnancy in muskoxen ( Ovibos moschatus) using samples that are commonly collected in harvester-based sampling programs: blood on filter paper and feces. We first evaluated three pregnancy tests, pregnancy-associated glycoproteins (PAG) on filter paper blood samples and fecal progesterone and estrogen metabolites (FPM and FEM), using 12 captive female muskoxen of known pregnancy status. Pregnancy diagnostics using PAG were highly sensitive (100 %) and specific (100 %), with a diagnostic threshold of 19.4 percent positivity (%P) relative to the positive control of the test kit. FPM and FEM diagnostic accuracy differed by hormone and time period. FPM was most accurate in mid-gestation and FEM most accurate in late gestation (sensitivities and specificities of 100 %), but both were overall less accurate than the PAG test during gestation. PAG %P followed a biphasic pattern during gestation, FPM peaked in mid-gestation, and FEM peaked in late-gestation. Following the captive trial, we applied these tests to fecal samples and blood on filter paper samples from 159 adult female muskoxen that were submitted by harvesters through community-based monitoring programs in the Canadian Arctic. The observed patterns of PAG, FPM, and FEM in wild muskoxen throughout gestation were similar to captive muskoxen, though with lower levels of the respective biomarker, requiring different diagnostic thresholds for each test. This work with captive and wild muskoxen provides guidelines for pregnancy diagnostics in muskoxen throughout gestation using samples that can be easily collected by harvesters, allowing for improved monitoring of difficult to access populations through community-based approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 teacher head, 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".