Identifyer for Zotero [beta]: convert plain-text citations in documents to live Zotero field code
I created a small program called Identifyer for Zotero to convert plain-text citatons in Word/ODT documents to live Zotero field codes. This is a beta and I am a sociologist, not a programmer, so it is essentially vibe coded. If you try it out, please comment on your experience, in particular if you have any technical issues.
https://github.com/JonasBaath/identifyer-for-zotero
The program essentially creates a copy of the document, strips it of all field codes from Zotero and EndNote (and acceppts all tracked changes), matches citations with your Zotero library, inserts citations with field codes, and allow you to export it. It is open for some ambiguity and asks you to review possible matches when there are several possible candidates in your library. In addition, you can get a txt output of citations without relevant sources. If the document has a bibliography, suggested matches with it are presented as well in the txt file and it also lists any posts in the bibliography that does not match any in line citations.
I have tested it with author-year-pagenr-citations but it is supposed to work with numbered citations as well.
https://github.com/JonasBaath/identifyer-for-zotero
The program essentially creates a copy of the document, strips it of all field codes from Zotero and EndNote (and acceppts all tracked changes), matches citations with your Zotero library, inserts citations with field codes, and allow you to export it. It is open for some ambiguity and asks you to review possible matches when there are several possible candidates in your library. In addition, you can get a txt output of citations without relevant sources. If the document has a bibliography, suggested matches with it are presented as well in the txt file and it also lists any posts in the bibliography that does not match any in line citations.
I have tested it with author-year-pagenr-citations but it is supposed to work with numbered citations as well.
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