Development of a competitive ELISA based on the LSDV A33 antigen
Bibliographic record
Abstract
Goatpoxvirus (GTPV), sheeppoxvius (SPPV), and the Lumpy skin disease virus (LSDV) is a Capripoxvirus belonging to the family poxviridae. They can cause significant economic losses in countries where this disease are endemic. However, effective and convenient diagnostic tools against sera antibody are not readily available until now. Toward this goal, a polyclonal antibody competitive enzyme-linked immunosorbent assay (c-ELISA) of detecting serogroup-specific antibody is established based on major LSDV antigen A33. Serum samples (n = 605) were collected to optimize the c-ELISA from different areas. The cut-off value for the c-ELISA was estimate using percent inhibition (PI) values. The diagnostic performance of test including sensitivity (sn) and specificity (sp) were obtained by receiver operator characteristic (ROC) analysis. Among these analysis, > 57.61% PI value was accepted as cut-off of the c-ELISA, the diagnostic sn an diagnostic sp were reached to 96.4% and 98.5%, at > 95% confidence interval. These results show that the developed competitive ELISA is sensitive, specific, and reliable, which make it appropriate for serological investigation.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".