Machine-learning predictions of high arsenic and high manganese at drinking water depths of the glacial aquifer system, northern continental United States (Q146021): Difference between revisions

From geokb
(‎Created a new Item: Added new publication item from USGS Pubs Warehouse)
 
(‎Changed an Item: added OpenAlex ID claim)
 
(2 intermediate revisions by the same user not shown)
Property / USGS Publications Warehouse IndexID
 
Property / USGS Publications Warehouse IndexID: 70220380 / rank
 
Normal rank
Property / USGS Publications Warehouse IndexID: 70220380 / reference
 
Property / addresses subject
 
Property / addresses subject: Arsenic Contamination in Natural Waters / rank
 
Normal rank
Property / addresses subject: Arsenic Contamination in Natural Waters / reference
 
Property / addresses subject
 
Property / addresses subject: Environmental Impact of Heavy Metal Contamination / rank
 
Normal rank
Property / addresses subject: Environmental Impact of Heavy Metal Contamination / reference
 
Property / addresses subject
 
Property / addresses subject: Metal-Induced Oxidative Stress and Health Effects / rank
 
Normal rank
Property / addresses subject: Metal-Induced Oxidative Stress and Health Effects / reference
 
Property / OpenAlex ID
 
Property / OpenAlex ID: W3144233634 / rank
 
Normal rank

Latest revision as of 15:45, 12 September 2024

a Article (Journal Article) published by American Chemical Society as part of series - Environmental Science & Technology
Language Label Description Also known as
English
Machine-learning predictions of high arsenic and high manganese at drinking water depths of the glacial aquifer system, northern continental United States
a Article (Journal Article) published by American Chemical Society as part of series - Environmental Science & Technology

    Statements

    0 references