Interlaboratory Comparison of <i>Porcine Circovirus-2</i> Indirect Immunofluorescent Antibody Test and Enzyme-Linked Immunosorbent Assay Results on Experimentally Infected Pigs
Bibliographic record
Abstract
A blinded interlaboratory assessment of the diagnostic agreement and accuracy of serologic tests for routine detection of antibodies against Porcine circovirus-2 (PCV-2), including indirect fluorescent antibody tests (IFATs) and enzyme-linked immunosorbent assays (ELISAs) was conducted in 7 North American laboratories. Serum samples were collected weekly, on trial days 0, 7, 14, 21, 28, 35, 42, and 49, from the following groups of animals: 1) negative controls (n = 7), 2) PCV-2a (n = 8), 3) PCV-2b (n = 8), 4) PCV-1 (n = 8), 5) PCV-2 vaccine A (n = 8; Ingelvac® CircoFLEX™), 6) PCV-2 vaccine B (n = 8; Circumvent® PCV2), and 7) PCV-2 vaccine C (n = 8; Suvaxyn® PCV2 One Dose). Results from each laboratory were analyzed by kappa and receiver operating characteristic (ROC) analysis. Kappa analysis indicated that, by trial day 49, IFATs had almost perfect agreement, in-house ELISAs had fair to almost perfect agreement, and commercially available anti-PCV-2 immunoglobulin G ELISAs (I or S) had moderate to substantial agreement. From trial days 14-49, the area under the ROC curve for the 2 laboratories that offered IFATs, the 4 laboratories that offered in-house ELISAs, and the 3 laboratories that used commercially available ELISAs ranged from 0.94 to 1.00, 0.72 to 1.00, and 0.95 to 1.00, respectively. However, test sensitivities varied based on laboratory-specific cutoffs that were used to dichotomize test results.
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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 | 0.024 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".