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- pretty_name: PubMed Cognitive Control Abstracts
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  license:
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  - cc-by-4.0
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  language:
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  - pubmed_gp3ada
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  ---
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  ## Dataset Description
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- - **Homepage:** [ArXiv preprint](https://arxiv.org/abs/1011.6217)
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- - **Repository:** [Linking Theories and Methods of Cognitive Control](https://github.com/morteza/cogtext)
 
 
 
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  - **Point of Contact:** [Morteza Ansarinia]([email protected])
 
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- We performed automated text analyses on a large body of scientific texts (385705 scientific abstracts) and created a joint representation of cognitive control tasks and constructs.
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- Abstracts were first mapped into an embedding space using GPT-3 and Top2Vec models. Document embeddings were then used to identify a task-construct graph embedding that grounds constructs on tasks and supports nuanced meaning of the constructs by taking advantage of constrained random walks in the graph.
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- **CogText** dataset contains a collection of PubMed abstracts, along with their GPT-3 embeddings and topic embeddings. See [CogText on GitHub](https://github.com/morteza/cogtext) for the details and codes.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- ## Citation
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  To cite the paper use the following entry:
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+ pretty_name: CogText PubMed Abstracts
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  license:
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  - cc-by-4.0
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  language:
 
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  - pubmed_gp3ada
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  ---
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+ # Dataset Card for CogText PubMed Abstracts
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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  ## Dataset Description
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+
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+ **CogText** dataset contains a collection of PubMed abstracts, along with their GPT-3 embeddings and topic embeddings. See [CogText on GitHub](https://github.com/morteza/cogtext) for the details and codes.
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+
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+ - **Homepage:** https://github.com/morteza/cogtext
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+ - **Repository:** https://github.com/morteza/cogtext
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  - **Point of Contact:** [Morteza Ansarinia]([email protected])
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+ - **Paper:** https://arxiv.org/abs/1011.6217
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+ ### Dataset Summary
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+ [Needs More Information]
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+ ### Supported Tasks and Leaderboards
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+ [Needs More Information]
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+ ### Languages
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+ English
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+ ## Dataset Structure
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+ ### Data Instances
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+ [Needs More Information]
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+ ### Data Fields
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+ [Needs More Information]
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+ ### Data Splits
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+ [Needs More Information]
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+
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+ ## Dataset Creation
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+ ### Curation Rationale
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+ [Needs More Information]
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+ ### Source Data
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+ #### Initial Data Collection and Normalization
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+ [Needs More Information]
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+ #### Who are the source language producers?
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+ [Needs More Information]
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+ ### Annotations
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+ #### Annotation process
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+ [Needs More Information]
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+ #### Who are the annotators?
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+ [Needs More Information]
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+ ### Personal and Sensitive Information
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+ [Needs More Information]
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+ ## Considerations for Using the Data
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+ ### Social Impact of Dataset
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+ [Needs More Information]
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+ ### Discussion of Biases
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+ [Needs More Information]
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+ ### Other Known Limitations
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+ [Needs More Information]
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+ ## Additional Information
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+ ### Dataset Curators
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+ [Needs More Information]
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+ ### Licensing Information
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+ [Needs More Information]
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+ ### Citation Information
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  To cite the paper use the following entry:
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