Evaluation of 2 ELISAs to determine <i>Borrelia burgdorferi</i> seropositivity in horses over a 12-month period
Bibliographic record
Abstract
The blacklegged tick ( Ixodes scapularis), which transmits Borrelia burgdorferi, the causative agent of Lyme disease, has undergone rapid range expansion in Ontario. In horses, Lyme disease remains an enigmatic disease, with limited understanding of the pathogenesis and many issues pertaining to selection and interpretation of laboratory tests. We evaluated B. burgdorferi seropositivity in naturally exposed horses over a 12-mo period and compared paired samples with 2 common serologic tests. Serum samples were collected in 2017, ~1 y after initial testing, from a cohort of 22 horses that were seropositive in a 2016 seroprevalence study. Samples were tested using a C6 ELISA and a multiplex ELISA targeting outer surface proteins A, C, and F. 1 y after initial testing, 14 of 22 (64%) horses remained seropositive; 7 (32%) were positive on the multiplex ELISA, 2 (9%) on C6 ELISA, and 5 (23%) on both tests. Repeatability was 100% for the C6 ELISA, and 95% for the multiplex ELISA, with no significant difference between paired sample multiplex titer values. Our results indicate strong intra-test reliability, although further investigation is required to determine the clinical significance of serologic testing.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".