Published 2025-01-01
“…The CIMS measurements were performed with an Orbitrap mass spectrometer coupled to a thermal desorption multi-scheme chemical ionization inlet unit (TD-MION-MS) with both negative and positive ionization modes utilizing <span class="inline-formula">Br<sup>−</sup></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">O</mi><mn mathvariant="normal">2</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="17pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="0874c22b59d147314cd2f8e88d131371"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-685-2025-ie00001.svg" width="17pt" height="16pt" src="acp-25-685-2025-ie00001.png"/></svg:svg></span></span>, <span class="inline-formula">H<sub>3</sub>O<sup>+</sup></span> and <span class="inline-formula">(CH<sub>3</sub>)<sub>2</sub>COH<sup>+</sup></span> (<span class="inline-formula">
AceH<sup>+</sup></span>) as reagent ions. We then trained two machine learning methods on these data: (1) random forest (RF) for classifying if a pesticide can be detected with CIMS and (2) kernel ridge regression (KRR) for predicting the expected CIMS signals. …”
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