Diagnosis of Transmissible Spongiform Encephalopathies in Animals: A Review
Bibliographic record
Abstract
Transmissible spongiform encephalopathies (TSEs) in animals include, among others, bovine spongiform encephalopathy (BSE), scrapie, chronic wasting disease, and atypical forms of prion diseases. Diagnosis of TSEs is based on identification of characteristic lesions or on detection of the abnormal prion proteins in tissues, often by use of their partial proteinase K resistance property. Correctly sampling of target tissues is of utmost importance as this has a considerable effect on test sensitivity. Most of the rapid or screening tests are based on ELISA or Western immunoblot (WB) analysis, and many are officially approved. Confirmatory testing is normally performed by use of histologic examination, immunohistochemical analysis, certain WB protocols, or detection of prion fibrils by use of electron microscopy (scrapie-associated fibril). The discriminatory methods for diagnostic use are mostly based on WB technology and provide initial identification of the prion strain, particularly for differentiation of BSE from scrapie in small ruminants. Definitive prion strain characterization is performed by use of bioassays, usually in mice. A burgeoning number of transgenic mice have been developed for TSE studies. Development of new tests with higher sensitivity and of more reliable diagnostic applications for live animals tested for food safety reasons is a rapidly developing field. Ultimately, the choice of a test for TSE diagnosis depends on the rationale for the testing.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".