Prevalence, fecal egg counts, and species identification of gastrointestinal nematodes in replacement dairy heifers in Canada
Bibliographic record
Abstract
Information is scarce regarding the epidemiology of gastrointestinal nematodes in Canadian dairy heifers. The objectives of this study were to estimate the prevalence and fecal egg counts of gastrointestinal nematodes in dairy heifers, and using a novel deep-amplicon sequencing approach, to identify the predominant gastrointestinal nematode species in Canadian dairy replacement heifers. Fresh environmental fecal samples (n = 2,369) were collected from replacement heifers on 306 dairy farms across western Canada, Ontario, Québec, and Atlantic Canada. Eggs per gram of feces (EPG) were determined using a modified Wisconsin double-centrifugation sugar flotation technique. Predominant nematode species at the farm level were identified by deep-amplicon nemabiome sequencing of the internal transcribed spacer-2 rDNA locus of nematode third-stage larvae. Generalized estimating equations were used to estimate predicted parasite prevalence and mean EPG in all heifers and by province, allowing for clustering within herds. Individual heifer egg counts ranged from 0 to 141 EPG (median: 0 EPG; interquartile range: 0 to 71 EPG). Gastrointestinal nematodes were detected in 20.9% (95% confidence interval: 17.2 to 24.6%) of heifers, and the predicted mean strongylid EPG accounting for clustering on farms was 1.1 (95% confidence interval: 0.6 to 1.6). The predominant parasite species were Cooperia oncophora and Ostertagia ostertagi. This is the first study in Canada to use a combination of deep-amplicon nemabiome sequencing and a traditional egg count method to describe the epidemiology of gastrointestinal nematodes in dairy heifers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".