Interlaboratory evaluation of an ELISA performed using a robotic automatic workstation versus manually testing for screening of Salmonella Typhimurium and Salmonella Choleraesuis antibodies in pig serum
Bibliographic record
Abstract
An enzyme-linked immunosorbent assay (ELISA) was developed to detect antibodies directed against Salmonella spp. in porcine serum. This assay is based on the Exiqon VetScreen TM Salmonella Covalent Mix-ELISA 96-well microtiter plates (Jauho et al, 2000). These microtiter plates are photochemically coated with Salmonella typhimurium and Salmonella choleraesuis PS- antigens 1,4,5,6,7, and 12 using the ExiqonDs patented photochemical method for covalent coupling of ligands to polymer surfaces (Wiuff et al, 2000). The assay was developed using an automatic robotic workstation. The Exiqon VetScreen TM Salmonella Covalent Mix-ELISA plates do not require any blocking steps. The developed assay showed 30 minutes incubation time for porcine serum samples as optimal, thereby giving a total assay time of two hours. In order to evaluate the assay, a comparison study between the FSD, Canada; Exiqon, Copenhagen Denmark was performed. A panel of positive and negative porcine serum samples was tested. The tests were carried out using a robotic automatic workstation and using a manually performed assay in three different laboratories (Exiqon and Danish Veterinary Lab, Denmark; Svanova, Sweden).The developed assay showed high specificity, sensitivity and excellent reproducibility. The interlaboratory study gave results of substantial agreement. No difference between manual and robotized performance could be identified. The automated ELISA can be used in high throughput screening of swine Salmonella spp. antibodies in seroprevalence studies.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".