Relative Distribution of Drugs in Decomposed Skeletal Tissue
Bibliographic record
Abstract
Skeletal tissues from a domestic pig exposed to amitriptyline, diazepam, and pentobarbital were analyzed to determine the relative distribution of these drugs in bone. Following drug exposure and euthanasia, remains were allowed to decompose outdoors to complete skeletonization between summer 2007 and fall 2009. Remains were recovered and separated according to bone type. Twelve different bone types were pulverized and sampled in triplicate. Each bone sample underwent methanolic extraction (96 h, 50 °C), followed by solid-phase extraction and gas chromatography-mass spectrometry in the selected ion monitoring mode. Mass-normalized assay responses underwent ANOVA with post-hoc testing, revealing bone type as a main effect for all three drugs, but not for the diazepam metabolite (nordiazepam). The assay response varied with respect to bone type by factors of 27, 39, and 20 for pentobarbital, diazepam, and amitriptyline, respectively. The relative distribution between bone type was qualitatively similar for the three administered drugs analyzed for, with the largest response obtained from rib for all three drugs. This is the first study, to the authors' knowledge, of the distribution of different drugs in various decomposed skeletal tissues in a controlled experiment using an animal model of comparable physiology to humans. These data have implications for the interpretive value of forensic drug measurements in skeletal tissues.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".