SHORT COMMUNICATION Seasonal changes of diagnostic potential in the detection of Anoplocephala perfoliata equine infections in the climate of Central Europe
Bibliographic record
Abstract
Abstract For this study, 724 gastrointestinal tracts of slaugh-ter horses were investigated to determine the prevalence, intensity of Anoplocephala perfoliata and tapeworm develop-ment stages over the second, third and fourth quarter of 2012 and the first quarter of 2013. For each positive horse, faecal samples were collected from the rectum or small colon for coproscopic examinations. The samples were analysed using dedicated modified sedimentation-flotation methods. In total, 52 horses were infected with A. perfoliata in the course of the study, with an overall prevalence of 7.2 %. The prevalence changed over the study period; however, not markedly. The overall mean of A. perfoliata abundance was 12.3 (3.23) and did not differ significantly between the quarters. Mean inva-sion intensity did not differ significantly between the quarters. The quantity of mature tapeworms did not differ significantly over the study period; however, there was a significant differ-ence in the number of immature tapeworms. The highest number of mature tapeworms was found in the first quarter of 2013. The number of detected tapeworm eggs rose signif-icantly over the study period. The total number of tapeworms did not have a significant influence on the presence/absence of detected eggs. However, there was a noticeable difference between the number of mature tapeworms and presence/ absence of eggs in faeces. This clearly indicates that the efficacy of the modified sedimentation-flotation method is influenced by seasonality, and therefore the most effective and reliable time for detection of A. perfoliata in equines is the first quarter of the year.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".