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Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.

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Title: Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.
Authors: Hong JK; Department of Environment and Energy Engineering, Chnonnam National University, Gwangju, 61186, Republic of Korea., Oh S; Department of Environmental research, Korea Institute of Civil engineering and building Technology (KICT), Gyeonggi-Do, 10223, Republic of Korea., Lee TK; Department of Environmental and Energy Engineering, Yonsei University, Wonju, 26493, Republic of Korea., Park S; Department of Environmental research, Korea Institute of Civil engineering and building Technology (KICT), Gyeonggi-Do, 10223, Republic of Korea; Department of Civil and Environmental Engineering, University of Science and Technology, Daejeon, 34113, Republic of Korea. Electronic address: srpark@kict.re.kr.
Source: Environmental research [Environ Res] 2025 Nov 15; Vol. 285 (Pt 1), pp. 122337. Date of Electronic Publication: 2025 Jul 10.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0147621 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-0953 (Electronic) Linking ISSN: 00139351 NLM ISO Abbreviation: Environ Res Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.
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  Data: <searchLink fieldCode="AU" term="%22Hong+JK%22">Hong JK</searchLink>; Department of Environment and Energy Engineering, Chnonnam National University, Gwangju, 61186, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Oh+S%22">Oh S</searchLink>; Department of Environmental research, Korea Institute of Civil engineering and building Technology (KICT), Gyeonggi-Do, 10223, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+TK%22">Lee TK</searchLink>; Department of Environmental and Energy Engineering, Yonsei University, Wonju, 26493, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Park+S%22">Park S</searchLink>; Department of Environmental research, Korea Institute of Civil engineering and building Technology (KICT), Gyeonggi-Do, 10223, Republic of Korea; Department of Civil and Environmental Engineering, University of Science and Technology, Daejeon, 34113, Republic of Korea. Electronic address: srpark@kict.re.kr.
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  Data: <searchLink fieldCode="JN" term="%220147621%22">Environmental research</searchLink> [Environ Res] 2025 Nov 15; Vol. 285 (Pt 1), pp. 122337. <i>Date of Electronic Publication: </i>2025 Jul 10.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>0147621 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1096-0953 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200139351%22">00139351 </searchLink><i>NLM ISO Abbreviation: </i>Environ Res <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.envres.2025.122337
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      – Code: eng
        Text: English
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        StartPage: 122337
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      – TitleFull: Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.
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            NameFull: Hong JK
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            NameFull: Oh S
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            NameFull: Lee TK
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              Text: 2025 Nov 15
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              Y: 2025
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