v0.16.2

Minor Changes:

• The OPTIMADEAdjuster model tuning class now includes more explicit provenance tracking through its references attribute, populated if the provider response includes "relations" to the references. As of now, many popular providers do not include these, but some, like alexandria, can be used and should populate references with a list of lists of DOI strings.
• The KS2022_randomSolutions's optional metadata dictionary, returned when returnMeta=True is passed to generate_descriptor function, now includes a list of KS2022 featurizations of each supercell expansion (i.e., iteration) under the individualResults field, which can be used in addition to the converged global ensemble. Among several use cases, users can use these to run ML models over subsets of the global ensemble and look at the prediction distributions to gain additional insights. E.g.:
  
• KS2022_randomSolutions implementation and code style have been generally improved.
• Appropriate documentation and tests were added.

Full Changelog: v0.16.1...v0.16.2