Bibliographic record
Abstract
To the Editor: We would like to report a rare problem we experienced with parenteral ondansetron (GlaxoWellcome). We have used ondansetron routinely for more than five years in our institutions. For the first time, we noticed 2 bottles of discolored ondansetron dispensed to the OR from the pharmacy along with other clear bottles of ondansetron with the same lot number and expiration date (Figure 1).Figure 1: Discoloration of Ondansetron. Ondansetron with the same lot number and expired date in the original bottles and draw up in 3ml plastic syringes. (Top) normal clear ondansetron. (Bottom) discolored ondansetron.Manufacturer’s instructions recommend discarding any discolored bottle of ondansetron. Although compliance with this instruction is obvious, the cause of the discoloration is not immediately apparent. Nor is it always easy for the anesthesiologist to detect discoloration of medication as they often work and administrate medications under poor lighting conditions, such as during laparoscopic surgery. Discoloration is even more difficulty to notice if the drug is already drawn into a plastic syringe (Figure 1), and the degree of discoloration may vary between vials. This would create the impression of a discolored vial and a clear vial, when the true situation was one strongly discolored and one less so. Fortunately, we detected the discolored medication prior to administration to our patient in a properly lit OR. This experience serves to remind us of the importance of carefully examining all medications under adequate lighting prior to administration. Ban C. H. Tsui, MSC, MD, FRCP(C) Dominic Cave, MBBS, FRCP(C)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".