Update README.md

README.md

@@ -71,14 +71,10 @@ You can scrape and clean all 16 guideline sources using our web scrapers and pre
 The dataset is intended for use in tasks related to text generation, specifically in the context of clinical practice guidelines. It can be employed for training language models and other natural language processing applications within the healthcare domain.
 
 
-[More Information Needed]
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 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
 
-The dataset may not be suitable for applications outside the realm of clinical practice guidelines or medical text analysis.
-
 [More Information Needed]
 
 ## Dataset Structure
@@ -101,7 +97,7 @@ Each row of the dataset represents one clinical practice guideline article, and
 
 <!-- Motivation for the creation of this dataset. -->
 
-The dataset was curated to provide a high-quality collection of clinical practice guidelines (CPGs) for the training of Large Language Models. 
+The dataset was curated to provide a high-quality collection of clinical practice guidelines (CPGs) for the medical training of LLMs. 
 
 Clinical practice guidelines are rigorously researched frameworks designed to guide healthcare practitioners and patients in making evidence-based decisions regarding diagnosis, treatment, and management. 
 They are compiled through a systematic process of collaborative consensus between experts to establish recommendations from the latest evidence on best practices that would maximize benefit in light of practical concerns such as available resources and context. As a super-synthesis of meta-analyses, they sit atop the `evidence pyramid' and form the basis of actionable evidence-based practice. 
@@ -125,10 +121,10 @@ Guidelines also contains a range of technical and conversational vocabulary with
 
 PDF documents were converted to text using [GROBID](https://github.com/kermitt2/grobid). 
 After extracting the raw text from each source, we cleaned data with an ad-hoc process to exclude irrelevant or repetitive content that did not contribute to the textual content, such as URLs, references, figures, table delimiters, and ill-formatted characters. 
-Additionally, the text was standardized to a unified format with section headers indicated by `#`, homogenous spacing `\n\n` separating paragraphs, and normalized lists formatted with `- ` bullet points. 
+This filtering procedure was performed differently for each source using a sample of 50 articles. Please note that this procedure is not perfect, as it may have removed useful information or kept superfluous content. We provide the `raw_text` for each article if you would like to perform your own cleaning step. 
+Additionally, the text was standardized to a unified format with hierarchical section headers indicated by `#`, homogenous spacing `\n\n` separating paragraphs, and normalized lists formatted with `- ` bullet points. 
 Finally, all samples were deduplicated using title matching, and articles that were too short or not English were filtered out. 
 
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 #### Who are the source data producers?
 
 <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
@@ -157,7 +153,7 @@ As the articles are publicly accessible, no personal or sensitive information is
 
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+[More Information Needed]
 
 ## Citation