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@@ -27,6 +27,14 @@ task_ids: []
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  # Dataset Card for "scientific_lay_summarisation"
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  ### Dataset Summary
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  This repository contains the PLOS and eLife datasets, introduced in the EMNLP 2022 paper "[Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
@@ -35,13 +43,15 @@ This repository contains the PLOS and eLife datasets, introduced in the EMNLP 20
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  Each dataset contains full biomedical research articles paired with expert-written lay summaries (i.e., non-technical summaries). PLOS articles are derived from various journals published by [the Public Library of Science (PLOS)](https://plos.org/), whereas eLife articles are derived from the [eLife](https://elifesciences.org/) journal. More details/anlaysis on the content of each dataset are provided in the paper.
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  Both "elife" and "plos" have 6 features:
 
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  - "article": the body of the document (including the abstract), sections seperated by "/n".
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- - "section_headings": the title of each section, seperated by "/n".
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  - "keywords": keywords describing the topic of the article, seperated by "/n".
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  - "title" : the title of the article.
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  - "year" : the year the article was published.
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  - "summary": the lay summary of the document.
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-
 
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  ### Supported Tasks and Leaderboards
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  Papers with code - [PLOS](https://paperswithcode.com/sota/lay-summarization-on-plos) and [eLife](https://paperswithcode.com/sota/lay-summarization-on-elife).
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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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- [More Information Needed]
 
 
 
 
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  ## Dataset Creation
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  "Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature"
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  Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton
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  EMNLP 2022
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- ```
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-
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- ### Contributions
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-
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- Thanks to [@TGoldsack1](https://github.com/TGoldsack1) for adding this dataset.
 
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  # Dataset Card for "scientific_lay_summarisation"
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+ - **Homepage:**
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+ - **Repository:** https://github.com/TGoldsack1/Corpora_for_Lay_Summarisation
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+ - **Paper:** [Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature](https://arxiv.org/abs/2210.09932)
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+ - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ - **Size of downloaded dataset files:** 850.44 MB
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+ - **Size of the generated dataset:** 1.32 GB
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+ - **Total amount of disk used:** 2.17 GB
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+
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  ### Dataset Summary
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  This repository contains the PLOS and eLife datasets, introduced in the EMNLP 2022 paper "[Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
 
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  Each dataset contains full biomedical research articles paired with expert-written lay summaries (i.e., non-technical summaries). PLOS articles are derived from various journals published by [the Public Library of Science (PLOS)](https://plos.org/), whereas eLife articles are derived from the [eLife](https://elifesciences.org/) journal. More details/anlaysis on the content of each dataset are provided in the paper.
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  Both "elife" and "plos" have 6 features:
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+
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  - "article": the body of the document (including the abstract), sections seperated by "/n".
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+ - "section_headings": the title of each section, seperated by "/n".
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  - "keywords": keywords describing the topic of the article, seperated by "/n".
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  - "title" : the title of the article.
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  - "year" : the year the article was published.
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  - "summary": the lay summary of the document.
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+
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+
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  ### Supported Tasks and Leaderboards
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  Papers with code - [PLOS](https://paperswithcode.com/sota/lay-summarization-on-plos) and [eLife](https://paperswithcode.com/sota/lay-summarization-on-elife).
 
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  ### Data Instances
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+ #### plos
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+
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+ - **Size of downloaded dataset files:** 425.22 MB
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+ - **Size of the generated dataset:** 1.05 GB
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+ - **Total amount of disk used:** 1.47 GB
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+
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+ An example of 'train' looks as follows.
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+ ```
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+ This example was too long and was cropped:
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+ {
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+ "summary": "In the kidney , structures known as nephrons are responsible for collecting metabolic waste . Nephrons are composed of a ...",
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+ "article": "Kidney function depends on the nephron , which comprises a 'blood filter , a tubule that is subdivided into functionally ...",
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+ "section_headings": "Abstract\nIntroduction\nResults\nDiscussion\nMaterials and Methods'",
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+ "keywords": "developmental biology\ndanio (zebrafish)\nvertebrates\nteleost fishes\nnephrology",
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+ "title": "The cdx Genes and Retinoic Acid Control the Positioning and Segmentation of the Zebrafish Pronephros",
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+ "year": "2007"
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+ }
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+
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+
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+ #### elife
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+
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+ - **Size of downloaded dataset files:** 425.22 MB
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+ - **Size of the generated dataset:** 275.99 MB
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+ - **Total amount of disk used:** 1.47 MB
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+
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+ An example of 'train' looks as follows.
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+ ```
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+ This example was too long and was cropped:
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+ {
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+ "summary": "In the USA , more deaths happen in the winter than the summer . But when deaths occur varies greatly by sex , age , cause of ...",
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+ "article": "In temperate climates , winter deaths exceed summer ones . However , there is limited information on the timing and the ...",
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+ "section_headings": "Abstract\nIntroduction\nResults\nDiscussion\nMaterials and methods",
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+ "keywords": "epidemiology and global health",
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+ "title": "National and regional seasonal dynamics of all-cause and cause-specific mortality in the USA from 1980 to 2016",
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+ "year": "2018"
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+ }
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+
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  ### Data Fields
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+ The data fields are the same among all splits.
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+ #### plos
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+ - `article`: a `string` feature.
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+ - `section_headings`: a `string` feature.
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+ - `keywords`: a `string` feature.
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+ - `title` : a `string` feature.
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+ - `year` : a `string` feature.
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+ - `summary`: a `string` feature.
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+
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+
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+ #### elife
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+ - `article`: a `string` feature.
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+ - `section_headings`: a `string` feature.
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+ - `keywords`: a `string` feature.
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+ - `title` : a `string` feature.
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+ - `year` : a `string` feature.
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+ - `summary`: a `string` feature.
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  ### Data Splits
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+ | name |train |validation|test|
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+ |------|-----:|---------:|---:|
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+ |plos | 24773| 1376|1376|
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+ |elife | 4346| 241| 241|
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+
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  ## Dataset Creation
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  "Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature"
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  Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton
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  EMNLP 2022
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+ ```