HIGHLIGHTS
SUMMARY
In recent years, Machine Learning (ML) applications (a sub-field of AI)1 have become increasingly widespread making it possible for researchers to work with larger amounts of data or detect patterns that would be hidden to the human eye (Eager et_al, 2020; Li et_al, 2017; Silver et_al, 2016). Specific CitSci tasks using the sub-class of ML, supervised learning (SL) for the classification of ecology images are most commonly reported on (Picek et_al, 2022; Willi et_al, 2018). Following these early attempts of ML adoption in CitSci, there have been several recent meta-analysis . . .
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