BLOOD COLLECTED ON FILTER PAPER FOR WILDLIFE SEROLOGY: EVALUATING STORAGE AND TEMPERATURE CHALLENGES OF FIELD COLLECTIONS
Bibliographic record
Abstract
Filter-paper (FP) blood sampling can facilitate wildlife research and expand disease surveillance. Previous work indicated that Nobuto FP samples from caribou and reindeer (Rangifer tarandus subspecies) had comparable sensitivity and specificity to serum samples (≥ 80% for both) in competitive enzyme-linked immunosorbent assays (cELISAs) for Brucella spp., Neospora caninum, and West Nile virus. The same sensitivity and specificity criteria were met in indirect ELISAs for Brucella spp., bovine herpesvirus type 1 (BHV-1), parainfluenza virus type 3 (PI-3), and bovine respiratory syncytial virus (BRSV), with adjusted FP thresholds used for PI-3 and BRSV. Comparable sensitivity and specificity values to serum were also observed for FP in virus neutralization (VN) assays for bovine viral diarrhea virus types I and II; however, reduced sensitivity is a potential limitation of FP samples in protocols that require undiluted serum (i.e., VN and N. caninum cELISA). We evaluated the performance of FP samples from reindeer and caribou in these nine assays after simulating potential challenges of high-latitude field collections: 1) different durations of storage and 2) different processing/storage regimes involving freezing or drying. Sample pairs (serum and FP) were collected from reindeer and caribou populations in 2007-10 and were tested in duplicate. Comparable performance to serum was defined as sensitivity and specificity ≥ 80%. In the storage experiments, FP performance was determined after 2 mo of storage dry at room temperature, and after two longer periods (variable depending on assay; up to 2 yr). After 1 yr, compared to frozen serum stored for the same period, sensitivity was ≥ 88% for all but two assays (68% BHV-1; 75% PI-3), and specificity remained >90%. A limited trial evaluated the effect of freezing FP samples as opposed to drying them for storage. There were no observed detrimental effects of freezing on FP sample performance, but rigorous investigation is warranted.
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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 | 0.007 | 0.010 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".