[[EVD - teams were more likely than single or pair-authored papers to cite atypical combinations of journals - @uzziAtypicalCombinationsScientific2013]]
[[EVD - papers with high median conventionality and high tail atypical combinations of journals they cited were 2x more likely than average to be in top 5 percent of citation distribution - @uzziAtypicalCombinationsScientific2013]]
[[EVD - papers with high median conventionality and high tail atypical combinations of journals they cited were 2x more likely than average to be in top 5 percent of citation distribution - @uzziAtypicalCombinationsScientific2013]]
@uzziAtypicalCombinationsScientific2013 makes the same move (journals as proxies of bodies of knowledge)
[[EVD - papers with high median conventionality and high tail atypical combinations of journals they cited were 2x more likely than average to be in top 5 percent of citation distribution - @uzziAtypicalCombinationsScientific2013]]
[[EVD - papers with high median conventionality and high tail atypical combinations of journals they cited were 2x more likely than average to be in top 5 percent of citation distribution - @uzziAtypicalCombinationsScientific2013]]
some questioning of the novelty measure in a later paper (@bornmannWeMeasureNovelty2019) comparing it to @uzziAtypicalCombinationsScientific2013's measure in terms of correlation to F1000 Prime ratings of biomed papers: depending on how you slice it, this is a plus or minus, since one key result in Wang is the asymmetry between home vs. foreign impact, and these F1000 tags are for papers that get recommended
also interesting is the idea of distant recombination, which feels like a mix of far conceptual combination and far analogies and outsider innovation, depending on the examples. don't find this to be particularly well theorized. but this connects very well to the way @uzziAtypicalCombinationsScientific2013 and @wangBiasNoveltyScience2017 think about things