Feline Cancer Prevalence in South Africa (1998 – 2005): Contrasts with the Rest of the World
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A paucity of information exists on the relative proportions, incidences or outcomes of diagnosis and treatment of feline cancer in South Africa. Standard texts of veterinary oncology quote data from the Northern hemisphere, and geographic differences are apparent. In this retrospective analysis, the electronic medical database of the Onderstepoort Veterinary Academic Hospital was analysed for feline cancer felines admissions for the period 1998 – 2005 (n = 100 out of N = 12,893 feline admissions, or 0.78% of total feline admissions). The average and median age of feline cancer felines was 7 and 9.5 years respectively. In contrast to published reports of US, Australian and European data where lymphosarcoma is the most common cancer affecting cats, squamous cell carcinoma (SCC) forms the predominant neoplasm (48% of all tumours). White or part-white cats were overrepresented in this group, which is consistent with greater ultraviolet light exposure. Lymphoma was the second most common diagnosis, followed by various carcinomas and adenocarcinomas. A large proportion (54%) of felines received some form of treatment.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it