Use of antibody titers measured via serum synergistic hemolysis inhibition testing to predict internal Corynebacterium pseudotuberculosis infection in horses
Bibliographic record
Abstract
OBJECTIVE: To estimate likelihood ratios (LRs) of correctly identifying internal Corynebacterium pseudotuberculosis infection in horses by measurement of antibody titers via serum synergistic hemolysis inhibition (SHI) testing. DESIGN: Retrospective case-control study. ANIMALS: 170 horses (171 records; 92 cases of C pseudotuberculosis infection and 79 controls). PROCEDURES: Medical records were reviewed, and horses were grouped on the basis of evidence of internal or external C pseudotuberculosis infection. The LRs and 95% confidence intervals for identification of internal C pseudotuberculosis infection by use of SHI test results were estimated. RESULTS: LRs for C pseudotuberculosis infection increased as antibody titers increased when all horses were included in analyses; LRs for detecting internal infection were significantly > 1 (null value) for reciprocal antibody titers ≥ 1,280 overall and > 160 when horses with external abscesses were excluded. Likelihood ratios for detecting internal infection did not differ from 1 (indicating no change in pretest-to-posttest odds of internal infection) when only horses with external C pseudotuberculosis infection (horses with external and internal abscesses vs those with external abscesses only) were included. The LR for detecting internal infection was 2.98 (95% confidence interval, 2.19 to 4.05) for horses with titers ≥ 512. CONCLUSIONS AND CLINICAL RELEVANCE: In the study population, higher titers were typically more indicative of active external or internal C pseudotuberculosis infection than of internal disease specifically. The SHI test was not a useful predictor of internal C pseudotuberculosis infection in horses with external abscesses but was useful in the absence of external disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".