Understanding Confusion: A Case Study of Training a Machine Model to Predict and Interpret Consensus From Volunteer Labels

Citizen science has become a valuable and reliable method for interpreting and processing big datasets, and is vital in the era of ever-growing data volumes. However, there are inherent difficulties in the generating labels from citizen scientists, due to the inherent variability between the members...

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Bibliographic Details
Main Authors: Ramanakumar Sankar, Kameswara Mantha, Cooper Nesmith, Lucy Fortson, Shawn Brueshaber, Candice Hansen-Koharcheck, Glenn Orton
Format: Article
Language:English
Published: Ubiquity Press 2024-12-01
Series:Citizen Science: Theory and Practice
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Online Access:https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/731
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