Comparison between available serologic tests for detecting antibodies against <i>Anaplasma phagocytophilum</i> and <i>Borrelia burgdorferi</i> in horses in Canada
Bibliographic record
Abstract
To investigate the agreement between available serologic tests for the detection of antibodies against Anaplasma phagocytophilum and Borrelia burgdorferi, 50 serum samples from horses of unknown clinical status and at low risk for infection were tested. In addition to a point-of-care enzyme-linked immunosorbent assay (pocELISA), the evaluated tests included 2 indirect fluorescent antibody tests (IFATs) for antibodies against A. phagocytophilum and an IFAT, an ELISA confirmed with Western blot, and the Lyme multiplex assay for antibodies against B. burgdorferi. For each pair-wise comparison between serologic tests, the difference in the proportion of seropositive results as well as kappa and the prevalence-adjusted, bias-adjusted kappa were calculated. The proportion of seropositive results differed significantly in each pairwise comparison of tests for detection of antibodies against A. phagocytophilum, and between the pocELISA and IFAT as well as between the pocELISA and Lyme multiplex assay for detection of antibodies against B. burgdorferi. Agreement based on kappa varied from poor to fair while agreement was improved when evaluating prevalence-adjusted, bias-adjusted kappa. Lack of agreement may be explained by differences in methodology between the evaluated tests, cross-reactivity or false-positive and false-negative tests. In addition to the limitations of serologic test interpretation in the absence of clinical disease, this data suggest that screening of horses for exposure to tick-borne diseases in nonendemic areas may not be 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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".