Non-invasive blood pressure measurement in animals: Part 1 - Techniques for measurement and validation of non-invasive devices.
Bibliographic record
Abstract
Arterial blood pressure is a common parameter evaluated in conscious and anesthetized veterinary species. Non-invasive blood pressure measurement techniques, such as Doppler ultrasonic flow detector and oscillometry, are attractive in certain animals due to their availability and ease of use. The greatest limitation to non-invasive blood pressure monitoring can be its inaccuracy, particularly in hypotensive or hypertensive patients and in certain species. Part 1 of this 2-part review summarizes the current techniques available to non-invasively measure arterial blood pressure in animals and discusses validation of non-invasive devices. Part 2 summarizes the veterinary literature that evaluates the use of non-invasive blood pressure measurement techniques in conscious and anesthetized species and develops general conclusions for proper use and interpretation of data from non-invasive blood pressure devices.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".