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Record W2031297502 · doi:10.1111/1556-4029.12550

Driving Under the Influence of Synthetic Cannabinoid Receptor Agonist <scp>XLR</scp>‐11

2014· article· en· W2031297502 on OpenAlexaff
Nikolas P. Lemos

Bibliographic record

VenueJournal of Forensic Sciences · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsSynthetic cannabinoidsCannabinoidAgonistCannabinoid receptorCannabinoid Receptor AgonistsRimonabantInverse agonistPharmacologyDriving under the influenceChemistryMedicinePoison controlReceptorInternal medicineEmergency medicineInjury prevention

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.363
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2014
Admission routes1
Has abstractyes

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