Comparison of Relative Distribution of Ketamine and Norketamine in Decomposed Skeletal Tissues Following Single and Repeated Exposures
Bibliographic record
Abstract
Bone was analyzed for ketamine and norketamine to examine whether different patterns of drug exposure could be discriminated. Rats received (intraperitoneally) one 75 mg/kg dose (Acute-1 and Acute-2 groups), three 25-mg/kg doses 1 hour apart (Repeated group), or nine single daily ketamine doses of 75 mg/kg followed by a 24-h washout period (Chronic group). Following euthanasia, all animals decomposed to skeleton outdoors. Ground samples of recovered bone underwent methanolic extraction and analysis by gas chromatography-mass spectrometry after solid-phase extraction. Drug levels (mass normalized response ratios) were compared across bone types and exposure pattern. Bone type significantly influenced drug level for the Acute-1 and Repeated dose groups, and the drug/metabolite level ratio (DMLR) for the Acute-1 group. Mean ketamine and norketamine level and DMLR varied by up to 8-fold, 7-fold and 3-fold, respectively, in the Acute-1 group, and by up to 24-fold, 5-fold and 10-fold, respectively, in the Repeated group. Drug level and DMLR differed significantly between the Acute-1 and Repeated groups for most bone types. In the Chronic group, only 1/16 and 4/16 samples were positive for ketamine and norketamine, respectively. All Acute-2 samples were positive for ketamine and norketamine. The Acute-2 and Chronic groups differed significantly in ketamine and norketamine levels, and DMLR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".