Using microsphere or fluorescein tracers and total oocyst output to measure ingestion of material following live-coccidiosis vaccinations
Bibliographic record
Abstract
One method of prevention of coccidiosis in broiler chickens raised without antibiotics relies on coccidiosis vaccination. Live-coccidiosis vaccines carry the risk for pathogenic effects if the Eimeria species overcycle. However, all chicks must receive an appropriate dose of Eimeria oocysts to induce immunity and reduce the risk of adverse effects. At the hatchery, coccidiosis vaccines are administered topically to boxes of chicks by spray or gel-droplet application. Determining the volume of vaccine ingested by individual chicks could provide a means of evaluating the success of different application methods. For each of 2 mass application methods (spray, gel-droplet), we used 3 quantification methodologies to determine the amount of vaccine material ingested by chicks: total oocyst counts from feces collected 5- to 8-days postvaccination; and counts of either microsphere or fluorescein tracers recovered from the gastrointestinal tract 30-min postvaccination. For each quantification methodology, chicks vaccinated via spray or gel-droplet application were compared to chicks vaccinated via oral gavage using the same concentration of oocysts per mL for all groups. Chicks vaccinated via gel-droplet application shed 10-fold more oocysts than those vaccinated by spray application. Individual chick consumption of vaccine material using tracers also revealed that chicks ingested more material following gel-droplet application than spray application, although the magnitude of the difference varied based on quantification methodology. The results of this study suggest that all 3 quantification methodologies can be used to help validate and improve mass vaccine application methods to ensure optimal ingestion, and therefore, coccidiosis vaccination success.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".