ArticleACS omega2019
Random Forest Processing of Direct Analysis in Real-Time Mass Spectrometric Data Enables Species Identification of Psychoactive Plants from Their Headspace Chemical Signatures.
Article in ACS omega, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- The Application of a Random Forest Classifier to ToF-SIMS Imaging Data.Journal of the American Society for Mass Spectrometry · 2024Article
- Mass Spectrometric Interrogation of Earwax: Toward the Detection of Ménière's Disease.ACS omega · 2023Article
- Combined ambient ionization mass spectrometric and chemometric approach for the differentiation of hemp and marijuana varieties of Cannabis sativa.Journal of cannabis research · 2023Article
- Article
- Forensic applications of DART-MS: A review of recent literature.Forensic chemistry (Amsterdam, Netherlands) · 2021Article
- Pharmacokinetics and Pharmacodynamics of Salvinorin A andPharmaceuticals (Basel, Switzerland) · 2021Review
- Detection of trace drugs of abuse in baby formula using solid-phase microextraction direct analysis in real-time mass spectrometry (SPME-DART-MS).Journal of forensic sciences · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The United Nations Office on Drugs and Crime has designated several "legal highs" as "plants of concern" because of the dangers associated with their increasing recreational abuse. Routine identification of these products is hampered by the difficulty in distinguishing them from innocuous plant materials such as foods, herbs, and spices. It is demonstrated here that several of these products have unique but consistent headspace chemical profiles and that multivariate statistical analysis processing of their chemical signatures can be used to accurately identify the species of plants from which the materials are derived. For this study, the headspace volatiles of several species were analyzed by direct analysis in real-time high-resolution mass spectrometry (DART-HRMS). These species include
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