Semi‐quantitative analysis of tramadol, dextromethorphan, and metabolites in decomposed skeletal tissues by ultra performance liquid chromatography quadrupole time of flight mass spectrometry
Bibliographic record
Abstract
Abstract The use of filtration/pass‐through extraction (FPTE) and ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry (UPLC–qTOF–MS) to detect tramadol (TRAM), dextromethorphan (DXM), and metabolites from skeletal remains is described. Rats (n=5) received 50 mg/kg tramadol and were euthanized by CO 2 asphyxiation approximately 30 minutes post‐dose. Rats (n=4) received 75 mg/kg dextromethorphan and were euthanized by CO 2 asphyxiation approximately 45 minutes post‐dose. Remains decomposed to skeleton outdoors and vertebral bones were collected. Bones were cleaned, dried, and pulverized to a fine powder. Bones underwent dynamic methanolic extraction followed by FPTE before analysis using UPLC–qTOF–MS. Recovery was at least 90% of maximal value within the first 10 minutes of methanolic extraction for all samples assayed. Analytical response was measured over the concentration range of 1–500 ng/mL, with precision and bias <20% in triplicate analyses of all calibrators, and a limit of detection of 1 ng/mL for TRAM, DXM, and all metabolites. The vertebral bone analyzed using this method detected TRAM, DXM, and their respective metabolites in all samples analyzed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".