Validation of the modified agglutination test for the detection of<i>Toxoplasma gondii</i>in free-range chickens by using cat and mouse bioassay
Bibliographic record
Abstract
The modified agglutination test (MAT) is one of the most commonly used tests for the detection of antibodies to Toxoplasma gondii in animal and human sera. The objective of the present study was to evaluate the diagnostic accuracy of the MAT and bioassay in free-range/backyard (FR) chickens (Gallus domesticus). Previously-published T. gondii test results from 2066 chickens from 19 countries were compiled for the present study. The frequency of isolation of T. gondii increased for MAT titres between 1:5 and 1:160, and ranged from 61 to 75% for antibody titres of 1:160, 1:320, and ⩾1:640. Twenty-three cats fed pooled hearts from a total of 802 FR seronegative (MAT, <1:5) chickens from several countries did not excrete oocysts, indicating a high negative predictive value of MAT because FR chickens would have been exposed to many microbes; cats are the most sensitive indicators of T. gondii infection in tissues and can excrete millions of oocysts after ingesting even a few bradyzoites. Of the 29 cats in this study, six cats, fed hearts pooled from 15-122 FR chickens, excreted oocysts; but these identifications were likely related to misidentification or prozone. Results of the present study support the validity of MAT for the detection of T. gondii infection in chickens.
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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 | 0.003 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".