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  ## Dataset Description
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- - **Homepage:**
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- - **Repository:**
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- - **Paper:**
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- - **Leaderboard:**
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- - **Point of Contact:**
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  ### Dataset Summary
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- This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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- ### Supported Tasks and Leaderboards
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- [More Information Needed]
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- ### Languages
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- [More Information Needed]
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  ## Dataset Structure
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- ### Data Instances
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- [More Information Needed]
 
 
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  ### Data Fields
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- [More Information Needed]
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- ### Data Splits
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- ## Dataset Creation
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- ### Curation Rationale
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- ### Source Data
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- #### Initial Data Collection and Normalization
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- [More Information Needed]
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- #### Who are the source language producers?
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- ### Annotations
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- #### Annotation process
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- #### Who are the annotators?
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- ### Personal and Sensitive Information
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- ## Considerations for Using the Data
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- ### Social Impact of Dataset
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- ### Discussion of Biases
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- ### Other Known Limitations
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- ## Additional Information
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- ### Dataset Curators
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- ### Licensing Information
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- ### Citation Information
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- ### Contributions
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  ## Dataset Description
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+ - **Homepage:** [BioCreative VII LitCovid Track](https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-5/)
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+ - **Paper:** [Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9428574/)
 
 
 
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  ### Dataset Summary
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+ Topic annotation in LitCovid is a multi-label document classification task that assigns one or more labels to each article. There are 7 topic labels used in LitCovid: Treatment, Diagnosis, Prevention, Mechanism, Transmission, Epidemic Forecasting, and Case Report. These topics have been demonstrated to be effective for information retrieval and have also been used in many downstream applications related to COVID-19.
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  ## Dataset Structure
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+ ### Data Instances and Data Splits
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+ - the training set contains 24,960 articles from LitCovid;
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+ - the validation set contains 6,239 articles from LitCovid;
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+ - the test set contains 2,500 articles from LitCovid;
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  ### Data Fields
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+ with the following fields retrieved from PubMed/LitCovid:
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+ • pmid: PubMed Identifier
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+ journal: journal name
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+ • title: article title
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+ abstract: article abstract
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+ • keywords: author-provided keywords
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+ pub_type: article type, e.g., journal article
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+ • authors: author names
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+ doi: Digital Object Identifier
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+ • label: annotated topics in list format indicating absence or presence of labels in the order 'Treatment,Diagnosis,Prevention,Mechanism,Transmission,Epidemic Forecasting,Case Report'
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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