Perioperative use of analgesics in dogs and cats by Canadian veterinarians in 2001.
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 random sample of 652 Canadian veterinarians was surveyed to determine perioperative use of analgesics in dogs and cats following common surgeries. The response rate was 57.8%. With the exception of taildocking in puppies, at least 85% of animals received preincisional analgesics, and 30% to 98.1% received postincisional analgesics. A similar survey was conducted in 1994; since then, analgesic usage has increased markedly, as have ratings of the pain caused by different surgeries. In 2001 most veterinarians (62%) used at least 2 classes of analgesic perioperatively. However, strong opioids, local anesthetics, and alpha-2 agonists were underused, and there was an overreliance on weak opioids (butorphanol, meperidine). Up to 12% of veterinarians did not use any analgesics. Nationally, this may have affected many animals monthly; for example, approximately 6000 dogs or cats undergoing ovariohysterectomy. Continuing education (provincial level) and review articles were considered effective ways to inform veterinarians about optimal analgesic practices.
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 | 0.000 | 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 | 0.000 | 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