The concern that Artificial Intelligence (AI) and Machine Learning (ML) are entering a "reproducibility crisis" has spurred significant research in the past few years. Yet with each paper, it is often unclear what someone means by "reproducibility". Our work attempts to clarify the scope of "reproducibility" as displayed by the community at large. In doing so, we propose to refine the research to eight general topic areas. In this light, we see that each of these areas contains many works that do not advertise themselves as being about "reproducibility", in part because they go back decades before the matter came to broader attention.

翻译：近年来，人工智能（AI）与机器学习（ML）正步入“可复现性危机”的担忧，已催生了大量相关研究。然而，每篇论文中“可复现性”的具体含义往往并不明确。本研究试图厘清学界整体所展现的“可复现性”概念范畴。为此，我们将现有研究归纳为八个主要主题领域。由此视角可见，每个领域均包含大量并未以“可复现性”自我标榜的研究成果，部分原因在于这些研究可追溯至该议题受到广泛关注的数十年前。