Driving Under the Influence of Synthetic Cannabinoid Receptor Agonist <scp>XLR</scp>‐11
Bibliographic record
Abstract
The case of a 22-year-old male Caucasian driver is presented. He was involved in a traffic collision. At the roadside, he displayed blank stare and mellow speech with a barely audible voice. A DRE found low body temperature, rigid muscle tone, normal pulse, lack of horizontal and vertical gaze nystagmus, nonconvergence of the eyes, dilated pupil size, and normal Pupillary reaction to light. A standard toxicology DUID protocol was performed on the driver's whole blood including ELISA and GC-MS drug screens with negative results. Additional drug screening was undertaken for bath salts and synthetic cannabinoid receptor agonists by LC-MS/MS by a commercial laboratory and identified the synthetic cannabinoid receptor agonist XLR-11 in the driver's blood. XLR-11 was subsequently quantified at 1.34 ng/mL. This is the first documented case involving a driver operating a motor vehicle under the influence of the synthetic cannabinoid receptor agonist XLR-11.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".