As it is often the case for social software services, online reference managers are becoming powerful and costless solutions to collect large sets of metadata, in this case collaborative metadata on scientific literature.
%A Author
%B Secondary Title (of a Book or Conference Name)
%C Place Published
%D Year
%E Editor /Secondary Author
%F Label
%G Language
%H Translated Author
%I Publisher
%J Journal Name
%K Keywords
%L Call Number
%M Accession Number
%N Number (Issue)
%O Alternate Title
%P Pages
%Q Translated Title
%R DOI
%S Tertiary Title
%T Title
%U URL
%V Volume
%W Database Provider
%X Abstract
%Y Tertiary Author / Translator
%Z Notes
%0 Reference Type
%1 Custom 1
%2 Custom 2
%3 Custom 3
%4 Custom 4
%6 Number of Volumes
%7 Edition
%8 Date
%9 Type of Work
%? Subsidiary Author
%@ ISBN/ISSN
%! Short Title
%# Custom 5
%$ Custom 6
%] Custom 7
%& Section
%( Original Publication
%) Reprint Edition
%* Reviewed Item
%+ Author Address
%^ Caption
%> File Attachments
%< Research Notes
%[ Access Date
%= Custom 8
%~ Name of Database
Command line:
```bash
jupyter nbconvert --to latex --TagRemovePreprocessor.remove_cell_tags='{"skip"}' --TagRemovePreprocessor.enabled=True 'nb.ipynb'
```
Also, to use it via python you need to enable the `TagRemoveProcessor` manually.
See: [source](https://stackoverflow.com/q/58564376/991496)
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