Relative Distribution of Ketamine and Norketamine in Skeletal Tissues Following Various Periods of Decomposition
Bibliographic record
Abstract
Skeletal tissues (rat) were analyzed for ketamine (KET) and norketamine (NKET) following acute ketamine exposure (75 mg/kg i.p.) to examine the influence of bone type and decomposition period on drug levels. Following euthanasia, drug-free (n = 6) and drug-positive (n = 20) animals decomposed outdoors in rural Ontario for 0, 1, or 2 weeks. Skeletal remains were recovered and ground samples of various bones underwent passive methanolic extraction and analysis by GC-MS after solid-phase extraction. Drug levels, expressed as mass normalized response ratios, were compared across tissue types and decomposition periods. Bone type was a main effect (p < 0.05) for drug level and drug/metabolite level ratio (DMLR) for all decomposition times, except for DMLR after 2 weeks of decomposition. Mean drug level (KET and NKET) and DMLR varied by up to 23-fold, 18-fold, and 5-fold, respectively, between tissue types. Decomposition time was significantly related to DMLR, KET level, and NKET level in 3/7, 4/7, and 1/7 tissue types, respectively. Although substantial sitedependence may exist in measured bone drug levels, ratios of drug and metabolite levels should be investigated for utility in discrimination of drug administration patterns in forensic work.
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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".