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  "Title": "Ionization efficiency prediction and quantification of\nunidentified chemicals",
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  "Description": "MS2Quant harvests pre-trained xgbTree algorithm-based\nionization efficiency prediction model. Using strucutral\ninformation (SMILES) or predicted fingerprints calculated with\nSIRIUS+CSI_FingerID software, ionization efficiency can be\npredicted. If calibrants have been measured together with\nsuspects subject to quantification, predicted ionization\nefficiencies can be converted into measurement-specific\nresponse factors and concentration of unknown chemcals can be\nestimated.",
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