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Provide a human-readable description of the reason that the value is uncertain/problematic.
Produce a "best guess" value (that is problematic)
Provide an identifier to allow uncertain values to be acknowledged (un-tagged).
Identify a procedure by which the user can address the error / repairing the value.
Optionally provide a facility for sampling alternative values.
1-3 are the critical features.
4 and 5 are useful support, although the current (heavy-weight) implementation of overriding the model value isn't the only way to implement repairs.
6 hasn't been exploited in a long time. It's also generally one of the weakest points whenever I present Mimir. However, the feature is useful for research purposes, and might provide some benefits for applying Mimir to simulation workloads (as opposed to data cleaning)
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