Non-dietary risk factors for gastric dilatation-volvulus in large and giant breed dogs
Bibliographic record
Abstract
OBJECTIVE: To identify non-dietary risk factors for gastric dilatation-volvulus (GDV) in large breed and giant breed dogs. DESIGN: Prospective cohort study. ANIMALS: 1,637 dogs > or = 6 months old of the following breeds: Akita, Bloodhound, Collie, Great Dane, Irish Setter, Irish Wolfhound, Newfoundland, Rottweiler, Saint Bernard, Standard Poodle, and Weimaraner. PROCEDURE: Owners of dogs that did not have a history of GDV were recruited at dog shows, and the dog's length and height and the depth and width of its thorax and abdomen were measured. Information concerning the dog's medical history, genetic background, personality, and diet was obtained from the owners, and owners were contacted by mail and telephone at approximately 1-year intervals to determine whether dogs had developed GDV or died. Incidence of GDV, calculated on the basis of dog-years at risk for dogs that were or were not exposed to potential risk factors, was used to calculate the relative risk of GDV. RESULTS AND CLINICAL RELEVANCE: Cumulative incidence of GDV during the study was 6% for large breed and giant breed dogs. Factors significantly associated with an increased risk of GDV were increasing age, having a first-degree relative with a history of GDV, having a faster speed of eating, and having a raised feeding bowl. Approximately 20 and 52% of cases of GDV among the large breed and giant breed dogs, respectively, were attributed to having a raised feed bowl.
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 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 | 0.000 | 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) | 0.001 | 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".