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20202026
most citedTag N' Train: A Technique to Train Improved Classifiers on Unlabeled Data

99 citations · 191 across the 16 of their papers we have counts for

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astro-ph.GA2021

Merger or Not: Accounting for Human Biases in Identifying Galactic Merger Signatures

Erini Lambrides, Duncan J. Watts, Marco Chiaberge +9

Significant galaxy mergers throughout cosmic time play a fundamental role in theories of galaxy evolution. The widespread usage of human classifiers to visually assess whether gala…