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    • Global patterns and predictions of seafloor biomass using random forests 

      Wei, Chih-Lin; Rowe, G.T.; Escobar-Briones, E.; Boetius, A.; Soltwedel, T.; Caley, M.J.; Soliman, Y.; Huettmann, F.; Qu, F.; Yu, Z.; Pitcher, C.R.; Haedrich, R.L.; Wicksten, M.K.; Rex, M.A.; Baguley, J.G.; Sharma, J.; Danovaro, R.; MacDonald, I.R.; Nunnally, C.C.; Deming, J.W.; Montagna, P.; Levesque, M.; Weslawsk, J.M.; Wlodarska-Kowalczuk, M.; Ingole, B.S.; Bett, B.J.; Billett, D.S.M.; Yool, A.; Bluhm, B.A.; Iken, K.; Narayanaswamy, B.E. (Public Library of Science, 2010)
      A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random ...