Field Validation of a Commercial Blocking ELISA to Differentiate Antibody to Transmissible Gastroenteritis Virus (TGEV) and Porcine Respiratory Coronavirus and to Identify TGEV-Infected Swine Herds
Bibliographic record
Abstract
A commercially available blocking ELISA was analyzed for its ability to identify antibodies to porcine coronaviruses (transmissible gastroenteritis virus [TGEV] or porcine respiratory coronavirus [PRCV]), to differentiate antibodies to TGEV and PRCV, and to identify TGEV-infected herds. Nine sera from uninfected pigs, 34 sera from 16 pigs experimentally infected with TGEV, and sera from 10 pigs experimentally infected with PRCV were evaluated using both the TGEV/PRCV blocking ELISA and a virus neutralization (VN) assay. The ELISA was not consistently effective in identifying pigs experimentally infected with TGEV until 21 days postinfection. Sera from 100 commercial swine herds (1,783 sera; median 15 per herd) were similarly evaluated using both tests. Thirty of these commercial herds had a clinical history of TGEV infection and a positive TGEV fluorescent antibody test recorded at necropsy within the last 35 months, while 70 herds had no history of clinical TGEV infection. The blocking ELISA and the VN showed good agreement (kappa 0.84) for the detection of porcine coronavirus antibody (TGEV or PRCV). The sensitivity (0.933) of the ELISA to identify TGEV-infected herds was good when considered on a herd basis. The ELISA was also highly specific (0.943) for the detection of TGEV-infected herds when the test results were evaluated on a herd basis. When sera from specific age groups were compared, the ELISA identified a greater proportion (0.83) of pigs in herds with TGEV antibody when suckling piglets were used. In repeatability experiments, the ELISA gave consistent results when the same sera were evaluated on different days (kappa 0.889) and when sera were evaluated before and after heating (kappa 0.888). The blocking ELISA was determined to be useful for herd monitoring programs and could be used alone without parallel use of the VN assay for the assessment of large swine populations for the detection of TGEV-infected herds.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".