Development of a high-resolution paper-spray mass spectrometry method using street drugs for the early detection of emerging drugs in the unregulated supply
Bibliographic record
Abstract
Adulteration of the unregulated opioid supply has contributed to increasing numbers of overdose deaths in North America. Harm-reduction drug checking has emerged as a strategy to address increasing adulteration rates by providing information about sample composition to people who use drugs. While paper-spray mass spectrometry is capable of trace detection for drug checking, the presence of newly emerging substances often goes undetected if not included in the targeted analysis method. High-resolution mass spectrometry has not been widely used in drug-checking efforts to date, but it has advanced capabilities to facilitate the detection of newly emerging substances. We present a high-resolution paper-spray mass spectrometry method developed for the detection of newly emerging compounds in the street-drug supply. The method was used to analyze a selection of opioid samples received at a drug-checking service in Victoria, British Columbia, Canada. Using this approach, newly emerging adulterants, precursors and byproducts were identified in the local street-drug supply.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".