Epidemiological studies of gastrointestinal nematodes in sheep flocks in Ontario and Quebec, Canada
Bibliographic record
Abstract
This thesis is an investigation of the prevalence and distribution of gastrointestinal nematodes (GINs) in sheep production systems in Canada and a review of the effectiveness of selected alternative treatments (ATs) for the prevention or control of GINs in sheep under field conditions. Two main studies were conducted. First, a systematic review-meta-analysis (SR-MA) was conducted on selected ATs against GINs in sheep. Secondly, a two-year longitudinal study was carried out (May 2006 - March 2008) on selected certified organic (CO, n=8), non-certified organic (NCO, n=16) and conventional (C, n=8) sheep farms in Ontario and Quebec, to study the prevalence, distribution and potential risk factors associated with the presence of GINs. Additionally, correlations between clinical parameters and fecal egg counts were investigated. In the SR-MA, the heterogeneity among 51 studies varied by study design and outcome type. MA of challenge studies (ChS) that evaluated nutraceuticals (bioactive forages containing condensed tannins) showed a significant median difference (MD) in fecal egg counts (FECs) of 1.38 (P=0.05), favouring treatment groups. Controlled studies and ChS that investigated genetic resistance, showed a significant MD of 3.93 (P=0.02) and non-significant MD of 4.9 FEC (P=O.06), respectively, with moderate (54%) and low (9.5%) heterogeneity, respectively. In the longitudinal study, there were non-significant differences (P>O.05) between FEC levels by farming type using a mixed linear model. However, there was a significant three-way interaction between province, sheep age and sampling month. In general, the distribution pattern of FECs for ewes and lambs varied by province and sampling period. Ewes showed their highest FEC peak during the spring season (April in ON and May in QC), while in lambs FECs peaked during the summer (July-August in ON and August-September in QC). Results from correlation models indicated that none of the clinical parameters evaluated to estimate GIN burden (scores for body condition, dag, fecal consistency and FAMACHA) were highly correlated with PCV or FECs. The information provided in this thesis is important for further studies on ATs for the control of GINs in sheep and future studies in Canada on topics such as 'hypobiosis' or the overwintering survival of sheep GIN infective larvae.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".