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Description
Submitting Author: DV Klopfenstein, PhD (@dvklopfenstein)
Package Name: pmidcite
One-Line Description of Package: Download "Cited by" data from the NIH for any paper with a PubMed ID from the cli
Repository Link: https://github.com/dvklopfenstein/pmidcite
EiC: TBD
Code of Conduct & Commitment to Maintain Package
- I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
- I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.
Description
Include a brief paragraph describing what your package does:
- Improve your literature search: Sort through papers faster; Make your lit search reproducible;
- Quickly download citation data for any PubMed ID (PMID) with with minimal typing on the command line. Citation data includes citation counts (aka "CitedBy" counts) and the performance of the paper in its co-citation network.
- Download a single line containing all the citation and reference counts, the number of authors, the first author's last name, and the title for each researcher-given PMID by default.
- Download all citation data: One line for each citing paper and optionally one line for each reference using the verbose option.
- MeSH (PubMed's Medical Subject Headings) keywords related to studies focusing on human, animal, and/or molecular/cellular biology are indicated as present if they are associated with the paper.
- Published in Research Synthesis Methods: http://dx.doi.org/10.1002/jrsm.1456
- PubMed: https://pubmed.ncbi.nlm.nih.gov/33031632/
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Scope
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Please indicate which category or categories this package falls under:
- Data retrieval
- Data extraction
- Data processing/munging
- Data deposition
- Data validation and testing
- Data visualization
- Workflow automation
- Citation management and bibliometrics
- Scientific software wrappers
- Database interoperability
Domain Specific
- Geospatial
- Education
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Explain how and why the package falls under these categories (briefly, 1-2 sentences). For community partnerships, check also their specific guidelines as documented in the links above. Please note any areas you are unsure of:
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Who is the target audience and what are the scientific applications of this package?
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Are there other Python packages that accomplish similar things? If so, how does yours differ?
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