Development of a methamphetamine chemical profiling program in Quebec, Canada for use in an intelligence perspective
Bibliographic record
Abstract
This paper describes a new method for the chemical profiling of seized methamphetamine tablets. This method was performed for the first time in Quebec, Canada, at the Laboratoire de sciences judiciaires et de médecine légale (LSJML, Provincial Forensic Laboratory). The main objective was to provide information related to the production and trafficking of methamphetamine tablets in the province of Quebec. Samples were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) and 12 relevant impurities were selected to establish the chemical class. Data were pretreated by the normalization to the sum of peak responses followed by the square roots. The Manhattan distance was then calculated between population of linked samples and unlinked samples. The method proved to efficiently discriminate between the two populations. A comprehensive database containing the profiles of all analyzed samples was established and continues to be updated. The database incorporates information about purity, chemical class, presence of cutting agents and physical characteristics of each specimen. If systematically applied, this methodology should highlight connections between ongoing cases and those stored in the database, as well as facilitate comparisons between preselected cases based on traditional police casework. Integrating the results of methamphetamine tablet chemical profiling with other pertinent law enforcement data will yield valuable tactical and operational intelligence as well as strategic intelligence. This project brings an additional tool to investigators with the differentiation of linked and unlinked methamphetamine specimens. Although further research is required to determine the tool's capacity to understand methamphetamine production and distribution networks, it shows potential for contributing to efforts against illicit production and trafficking in the province of Quebec, Canada.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".