COMPARISON OF AMIKACIN PHARMACOKINETICS IN A KILLER WHALE (ORCINUS ORCA) AND A BELUGA WHALE (DELPHINAPTERUS LEUCAS)
Bibliographic record
Abstract
Amikacin, an aminoglycoside antimicrobial, was administered to a killer whale (Orcinus orca) and a beluga whale (Delphinapterus leucas) for the treatment of clinical signs consistent with gram-negative aerobic bacterial infections. Dosage regimens were designed to target a maximal plasma concentration 8-10 times the minimum inhibitory concentrations of the pathogen and to reduce the risk of aminoglycoside toxicity. Allometric analysis of published pharmacokinetic parameters in mature animals yielded a relationship for amikacin's volume of distribution, in milliliters, given by the equation Vd = 151.058(BW)1.043. An initial dose for amikacin was estimated by calculating the volume of distribution and targeted maximal concentration. With this information, dosage regimens for i.m. administration were designed for a killer whale and a beluga whale. Therapeutic drug monitoring was performed on each whale to assess the individual pharmacokinetic parameters. The elimination half-life (5.99 hr), volume of distribution per bioavailability (319 ml/kg). and clearance per bioavailability (0.61 ml/min/kg) were calculated for the killer whale. The elimination half-life (5.03 hr), volume of distribution per bioavailability (229 ml/kg). and clearance per bioavailability (0.53 ml/min/kg) were calculated for the beluga whale. The volume of distribution predicted from the allometric equation for both whales was similar to the calculated pharmacokinetic parameter. Both whales exhibited a prolonged elimination half-life and decreased clearance when compared with other animal species despite normal renal parameters on biochemistry panels. Allometric principles and therapeutic drug monitoring were used to accurately determine the doses in these cases and to avoid toxicity.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".