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Discover LudwigExact(1)
The text from the recovered citations is processed to identify sentence boundaries and protein/gene mentions (Whatizit-UniProt), which are then mapped to UniProt identifiers.
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Furthermore, we recovered 97 (4.8%) citations in which Wikipedia was cited in place of an original research study.
These citations were recovered from PubMed selecting English abtracts containing novel human mutations, targeting formulaic mentions.
We searched for additional studies in personal reference lists and citation sections of recovered articles.
After discarding those that did not have citations in Google Scholar, a total search of 1811 articles was obtained, and after the filtering by decade, number of citations and repetitions in the databases in accordance with the selection criteria of the sample laid out in the procedure and considering that from the 1960s, only five of the documents recovered met the search and citation criteria.
The authors also reviewed publications in personal reference lists and citation sections of the recovered articles.
They considered 70 PDB records with 13 mutations, and the corresponding primary citations of those records, finding that <10% of these mutations could be recovered from abstracts, while >70% were able to be recovered from the full-text articles.
He recovered.
They recovered.
Recovered gear.
Madrid recovered.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com