Morbidity of Swedish horses insured for veterinary care between 1997 and 2000: variations with age, sex, breed and location
Bibliographic record
Abstract
The aim of this study was to evaluate the potential usefulness of the database maintained by the Swedish insurance company Agria for providing disease statistics on Swedish horses. The demography of the horses insured for veterinary care during the period 1997 to 2000 was recorded and the incidence of morbidity, defined as horses that required veterinary care that cost more than the policy excess, was calculated. Yearly incidences were calculated for horses that required veterinary care at least once, first overall, and then for horses with complete insurance, by sex, age, breed group, breed, location and human population density. Poisson regression was applied to a multivariable model to produce estimates of relative risk adjusted for other factors in the model, such as age. The total number of horse-years at risk for those with complete insurance was over 72,000 each year. The annual incidence rate for horses that required veterinary care at least once varied from 1080 to 1190 events per 10,000 horse-years at risk; for geldings the averaged incidence rate was 1398 events, for mares it was 1042 events, and for stallions it was 780 events per 10,000 horse-years at risk. There were considerable variations in incidence rate between breeds.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".