Cross-validation of the RT-QuIC assay for the antemortem detection of chronic wasting disease in elk
Bibliographic record
Abstract
Chronic wasting disease is a progressively fatal, horizontally transmissible prion disease affecting several members of the cervid species. Conventional diagnosis relies on ELISA or IHC evaluation using tissues collected post-mortem; however, recent research has focused on newly developed amplification techniques using samples collected antemortem. The present study sought to cross-validate the real-time quaking-induced conversion assay (RT-QuIC) evaluation of rectal biopsies collected from an elk herd with endemic CWD, assessing both binary positive/negative test results as well as relative rates of amplification between laboratories. We found that results were correlative in both categories across all laboratories performing RT-QuIC, as well as to conventional IHC performed at a national reference laboratory. A significantly higher number of positive samples were identified using RT-QuIC, with results seemingly unhindered by low follicle counts. These findings support the continued development and implementation of amplification assays in the diagnosis of prion diseases of veterinary importance, targeting not just antemortem sampling strategies, but post-mortem testing approaches as well.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".