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This paper studies why different possible explanations for the same observations can remain hard to distinguish, even when large amounts of data are available. Its central claim is that the problem is often not lack of data, but lack of enough independent and usable ways of observing the system. The paper introduces a mathematical lemma showing when different candidate states become observationally indistinguishable, and when separability can be restored by adding the right kinds of observation channels. It also explains that more channels are not automatically better: they must provide genuinely new information, and they must do so without raising the overall uncertainty too much. The result is a practical framework for thinking about observation portfolios in science, engineering, finance, and AI—focusing on the quality and independence of viewpoints rather than raw measurement count alone. A final example uses the James Webb Space Telescope’s “Little Red Dots” debate to illustrate how multiple real possibilities can remain blended together when observation geometry is too limited.Note: PDF conversion crated some font issues, but do not effect content.
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Joseph DeMase (2026) studied this question.
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