A comparison of alfaxalone and propofol on intraocular pressure in healthy dogs
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To compare the effects of alfaxalone and propofol on intraocular (IOP) pressure in the canine eye. ANIMALS STUDIED: Twenty-three healthy adult dogs. PROCEDURES: Dogs were randomized to receive intravenous propofol (n = 11) or alfaxalone (n = 12) until loss of jaw tone, 20 min after intravenous premedication (acepromazine 0.02-0.03 mg/kg and hydromorphone 0.05-0.1 mg/kg). IOP was measured at baseline (BL), 20 min postpremedication (postpremed), loss of jaw tone (postinduct), and immediately following orotracheal intubation (postintub). Between- and within-treatment effects were analyzed with two-way and one-way repeated measures ANOVA with Bonferroni's post hoc test, respectively. P < 0.05 was considered significant. RESULTS: No significant IOP differences were detected between alfaxalone or propofol groups at any time point (P > 0.05). Propofol: IOP did not change between BL (15.5 ± 2.7 mmHg) and postpremed (16.2 ± 3.6 mmHg, P > 0.05), or postinduct (19.1 ± 5.2 mmHg) and postintub (21.0 ± 4.6 mmHg, P > 0.05), but differed significantly between BL and postinduct (P < 0.0001), and postintub (P < 0.0001). Alfaxalone: IOP did not change between BL (15.7 ± 2.8 mmHg) and postpremed (15.3 ± 4.1 mmHg, P > 0.05), or postinduct (19.2 ± 4.9 mmHg) and postintub (20.5 ± 4.5 mmHg, P > 0.05), but differed significantly between BL and postinduct (P < 0.01), and postintub (P < 0.0001). CONCLUSIONS: These data show a potentially clinically significant increase in IOP following induction with propofol or alfaxalone, but no difference between agents.
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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) | 0.001 | 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) | 0.001 | 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