paper = lens_id or DOI (whatever ID is chosen must be used for references as well)
mag = Lens.org fields_of_study (all lowercase, spaces replaced by underscores)
mesh = Lens.org mesh_terms.mesh_ids
venue = Lens.org Source Title
author = array of MAG ids.
reference = array of lens_ids or DOIs
scholarly_citations = array of scholarly_citations lens_ids.
text = title + abstract. (tokenize the text, remove all punctuation, and convert all characters to lowercase)
label = array of biomimicry functions (all lowercase, spaces replaced by underscores)
Take our 1375 labelled papers and put them in this JSON format
Example:
JSON field mappings to lens.org fields: https://support.lens.org/scholar-field-definitions/
paper = lens_id or DOI (whatever ID is chosen must be used for references as well) mag = Lens.org fields_of_study (all lowercase, spaces replaced by underscores) mesh = Lens.org mesh_terms.mesh_ids venue = Lens.org Source Title author = array of MAG ids. reference = array of lens_ids or DOIs scholarly_citations = array of scholarly_citations lens_ids. text = title + abstract. (tokenize the text, remove all punctuation, and convert all characters to lowercase) label = array of biomimicry functions (all lowercase, spaces replaced by underscores)
How to clean text in python: https://machinelearningmastery.com/clean-text-machine-learning-python/
Then put the JSON on a single line per paper in a
.json
file