Effect of signalment on the presentation of canine patients suffering from cranial cruciate ligament disease
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of signalment on the incidence and presentation of patients suffering from cranial cruciate ligament disease. METHODS: Data relating to 426 dogs (44 breeds) that met specific selection criteria were obtained from the hospital archive (2002 to 2008). Cases were followed up for 2 years. RESULTS: The breeds most commonly presented with cranial cruciate ligament disease were Labrador retriever (16%), Rottweiler (15%), golden retriever (12%) and boxer (9%). Rottweilers were significantly more likely (69%; P=0·05) to develop and present with (50%; P=0·03) bilateral cranial cruciate ligament disease. Rottweilers presenting with cranial cruciate ligament disease were significantly younger (median 977 days; P<0·0001) than other breeds; golden retrievers being significantly older at presentation (median 1994 days; P=0·004). Neither sex nor neutered status significantly affected the incidence of developing (P=0·77 and P=0·30, respectively) or presenting with (P=0·62 and P=0·35, respectively) bilateral cranial cruciate ligament disease. Entire dogs were significantly younger than neutered dogs at presentation (P=0·0004). Entire female dogs presented significantly younger than neutered females (P=0·0002), entire males (P=0·01) and neutered males (P=0·0001). CLINICAL SIGNIFICANCE: Breed affects the incidence of developing and presenting with bilateral cranial cruciate ligament disease. Breed and sex both affect the age that patients present with cranial cruciate ligament disease.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".