Bibliographic record
Abstract
High blood pressure (hypertension) is an common problem in geriatric cats. Routine measurement of blood pressure can contribute to optimal clinical care. Veterinary nurses play an important role in measurement of blood pressure in routine clinical practice. Successful measurement of blood pressure in cats requires attention to detail using a standardized protocol such as that outlined in this article. Veterinary nurses are well placed to apply such a standard procedure, thereby obtaining consistent and accurate results. Hypertension is often a hidden condition, masked by cats' incredible coping abilities. Blindness or hyphaema may be the first sign noticed by the owner. Even though blind cats can lead a relatively normal life, they often have an underlying disease associated with hypertension, such as chronic kidney disease and/or hyperthyroidism. However, some cats may have no underlying diseases detectable and their hypertension would be classified as idiopathic. Treatment using amlodipine besylate, a calcium channel blocker, has been shown to work most effectively in cats with hypertension. In the last few decades knowledge of hypertension has improved, however, many older cats are still not routinely having their blood pressure measured. The veterinary nurse is often under utilized in this area. Veterinary nurses should take a pro-active role in measuring blood pressure in cats, within the consulting room, with their owners present. It is only by performing routine, pre-emptive blood pressure measurement in the absence of clinical signs that development of end-organ damage, such as blindness, will be prevented.
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 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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".