Analysis of the Economic Impact of Neospora caninum in Ontario Dairy Cattle
Bibliographic record
Abstract
The difficult task of establishing the economic impact of Neospora caninum infection in dairy cattle is complicated by the broad parameters defining the effects of N. caninum infection. Estimates of the impact of the abortifacient effects have ranged from annual losses of $6.78 million (USD) in New Zealand to $35 million for California. $7.3 million is lost annually in Japan by decreased milk production in infected animals. A negative effect on milk production has not proven universal, yet assumptions regarding it are integral to an accurate economic estimate. This work describes the results of an analysis of the association between N. caninum infection and milk production in two Ontario dairy herd populations. In one group of cows from herds experiencing N. caninum-abortion problems (group A), seropositive animals produced 607 lb (276 kg) less 305-day milk than seronegative cows (n=1196, p<0.05). By contrast, in the second population of herds (group B), considered representative of Ontario, seropositive animals produced 332 lb (151 kg) more 305-day milk compared to seronegative cows (n=3162, p=0.10). The objective of this work was to quantify the economic effect of N. caninum infection in Ontario dairy cattle, considering the potential detrimental or enhancing effect of infection on milk production.
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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 | 0.000 | 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 | 0.001 | 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".