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References from Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning. Local targets link to admitted publications; unresolved targets remain external evidence.
Coastal zone tourism: a potent force affecting environment and society
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The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks
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Implementing and innovating marine monitoring approaches for assessing marine environmental status
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The future of biotic indices in the ecogenomic era: Integrating (e) DNA metabarcoding in biological assessment of aquatic ecosystems
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Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes
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Metabarcoding and machine learning analysis of environmental DNA in ballast water arriving to hub ports
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Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea
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Fecal source identification using random forest
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On the importance of training data sample selection in random forest image classification: a case study in peatland ecosystem mapping
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Learning from imbalanced data
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What drives forest fire in Fujian, China? Evidence from logistic regression and Random Forests
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