How do swine practitioners and veterinary pathologists arrive at a diagnosis of Clostridium perfringens type A enteritis in neonatal piglets?
Bibliographic record
Abstract
A questionnaire was administered to 22 veterinary practitioners and 17 veterinary pathologists to investigate the methods used for diagnosis of Clostridium perfringens type A enteritis in neonatal pigs. Practitioners generally diagnosed C. perfringens type A associated enteritis by age of onset of diarrhea (between 1 to 7 days of age). Most practitioners (95%) were moderately to very confident in their diagnosis. Pathologists generally diagnosed C. perfringens type A associated enteritis by combinations of isolation of the organism, genotyping or detecting the toxins of the organism, and ruling out other pathogens through histopathology. Almost half (41%) of the pathologists were not confident of their diagnosis. This study reports that the current diagnostic method for C. perfringens type A enteritis is not specific, and although many pathologists expressed reservations about making a diagnosis of C. perfringens type A enteritis, most practitioners were confident in their diagnosis, even though reported clinical signs of clostridial diarrhea are similar to those of a number of other enteric diseases.
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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 | 0.013 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".