Bibliographic record
Abstract
Transmissible spongiform encephalopathies (prion diseases) in animals may be associated with a zoonotic risk potential for humans as shown by the occurrence of variant Creutzfeldt-Jakob disease in the wake of the bovine spongiform encephalopathy epidemic. Thus, the increasing exposure of humans in North America to cervid prions of chronic wasting disease (CWD) in elk and deer has prompted comprehensive risk assessments. The susceptibility of humans to CWD infections is currently under investigation in different studies using macaques as primate models. The necessity for such studies was recently reinforced when disease-associated prion protein and its seeding activity were detected in muscles of clinically inconspicuous CWD-infected white-tailed deer. Increasing evidence points to the existence of different CWD strains, and CWD prions may also change or newly emerge over time. Therefore, CWD isolates examined in macaques should be characterized as precisely as possible for their molecular identity. On this basis other CWD field samples collected in the past, present or future could be systematically compared with macaque-tested inocula in order to assess whether they are covered by the ongoing risk assessments in primates. CWD typing by Fourier transform-infrared spectroscopy of pathological prion protein may provide a method of choice for this purpose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".