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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".