Datasets:
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Text Classification
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## Dataset Description
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- **Homepage:**
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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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### 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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### Data Fields
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[More Information Needed]
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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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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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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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[More Information Needed]
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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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