Specific causes of morbidity among Swedish horses insured for veterinary care between 1997 and 2000
Bibliographic record
Abstract
The principal aim of this study was to analyse the incidence of disease due to general and more specific causes among over 100,000 horses covered by complete insurance for veterinary care by a Swedish insurance company during 1997 to 2000. The database was used to calculate the rate of cause-specific morbidity in horses of different ages, sexes and breed groups kept in different regions with different human population densities. The joints were the most commonly affected part of the body, followed by unspecified/whole body, the skin and the digestive system. The most common specific diagnosis was fetlock arthritis, followed by lameness of undefined origin, other locomotor problems, traumatic injuries to the skin, arthritis in several joints, and colic. Geldings had the highest rate of at least one disease event in the joints, unspecified/whole body, skeletal or respiratory system, whereas in the other four major systems the difference between the sexes was marginal.
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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 | 0.002 | 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".