{"id":"W3040739689","doi":"10.1038/s41597-020-0534-3","title":"The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data","year":2020,"lang":"en","type":"article","venue":"Scientific Data","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":1766,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Manitoba; Centre de Géomatique du Québec; University of Saskatchewan; Canadian Forest Service; Environment and Climate Change Canada; University of British Columbia; University of Waterloo; Global Institute for Water Security; Université Laval; Natural Resources Canada; Ministère des Ressources naturelles et des Forêts; Ontario Drive & Gear (Canada); McMaster University","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Eddy covariance; Covariance; Pipeline (software); Computer science; Data mining; Statistics; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06542144998765222,"score_gpt":0.2774303750916456,"score_spread":0.2120089251039934,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}