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Record W3080445721 · doi:10.1002/ansa.202000083

Rapid and quantitative determination of fentanyls and pharmaceuticals from powdered drug samples by paper spray mass spectrometry

2020· article· en· W3080445721 on OpenAlexafffund
Scott A. Borden, Armin Saatchi, Erik T. Krogh, Chris G. Gill

Bibliographic record

VenueAnalytical Science Advances · 2020
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsVancouver Island UniversitySimon Fraser UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaVancouver Island University
KeywordsChromatographySlurryPharmaceutical drugPharmaceutical formulationMass spectrometryFentanylSample preparationDrugChemistryMaterials sciencePharmacologyMedicine

Abstract

fetched live from OpenAlex

Paper spray mass spectrometry is presented as a direct, quantitative tool for the measurement of pharmaceutical drugs and a variety of fentanyl analogs in solid samples and powder slurries with the ultimate goal of providing meaningful harm-reduction drug checking. Method development and validation was carried out for fentanyl analog slurries as a proxy for street drug samples. Lower limits of quantitation were determined to be 3.6-7.4 ng/g for fentanyl analogs in the pharmaceutical slurry matrix. Using 1 mg of solid sample, the method can quantify picogram quantities of these drugs, well below required thresholds for even the most potent fentanyl analogs. Quality control samples were prepared and used to assess method validity according to the Scientific Working Group for Forensic Toxicology (SWGTOX) guidelines. Performance metrics for both precision and accuracy were found to be within SWGTOX-recommended guidelines. Additionally, pharmaceutical tablets were used to demonstrate the applicability of the developed paper spray methodology for the direct qualitative and quantitative analysis of active ingredients in pharmaceutical powders deposited directly onto the paper spray substrate. A proposed workflow for rapid solid drug sample measurements is presented with potential applications for point-of-use street drug measurements and other solid sample matrices.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.339
Teacher spread0.308 · 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

Citations29
Published2020
Admission routes2
Has abstractyes

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