“Explain” in scientific discourse
By James A. Overton. 2013
48 citations recorded by the source corpus.
Subfields: History and Philosophy of Science, Molecular Biology, Statistics and Probability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In History and Philosophy of Science
- Tim Miller
- Gary Klein
- Robert R. Hoffman
- William J. Clancey
- Abigail Emrey
- Shane T. Mueller
- David William Aha
- D. Gunning
In Molecular Biology
- Tim Miller
- Gary Klein
- Robert R. Hoffman
- William J. Clancey
- Marco F. Duarte
- Jochen Garcke
- Bastian Bohn
- Ribana Roscher
In Statistics and Probability
- Tim Miller
- Gary Klein
- Robert R. Hoffman
- William J. Clancey
- Marco F. Duarte
- Jochen Garcke
- Ribana Roscher
- Abigail Emrey
Citations in the corpus
- Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, methodology): “In the fields of AI and philosophy of science, problem diagnosis, causal explanation, scientific discovery, and explanation are regarded as highly related or even overlapping (e.g., Darden, Machamer, and Crave, 2000; Overton, 2013; Shank, 1986).”
- Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, background): “Overton [140, 139] defines a model of scientific explanation.”
- Explainable Machine Learning for Scientific Insights and Discoveries (2019, background): “For scientific explanations, [30] identifies five broad categories to classify the large majority of objects that are explained in science: data, entities, kinds, models, and theories.”