BASF-AI/WikipediaEasy2GreenhouseVsEnantiopureClassification

---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: label_text
dtype: string
splits:
- name: train
num_bytes: 786170
num_examples: 908
- name: test
num_bytes: 208017
num_examples: 228
download_size: 578346
dataset_size: 994187
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
language:
- en
tags:
- chemistry
- wikipedia
- chemteb
pretty_name: Wikipedia Solid-state vs Colloidal Chemistry Binary Classification
size_categories:
- 1K<n<10K
---
# Wikipedia Greenhouse Gases vs Enantiopure Drugs Binary Classification
This dataset is derived from the English Wikipedia articles and is tailored for binary text classification tasks in the fields of environmental science and pharmaceutical chemistry. The dataset is divided into two classes based on the thematic content of the articles:
- Class 1 (**Greenhouse Gases**): This class includes articles that discuss various aspects of greenhouse gases. These are gases that trap heat in the Earth's atmosphere, contributing to the greenhouse effect and global warming. Topics may cover sources, types, impacts, and mitigation strategies related to greenhouse gases.
- Class 2 (**Enantiopure Drugs**): This class contains articles focused on enantiopure drugs. Enantiopure drugs are pharmaceutical compounds that consist of only one enantiomer (a molecule that is a mirror image of another molecule but cannot be superimposed on it). These drugs are significant in medicinal chemistry due to their specific interactions with biological systems, leading to desired therapeutic effects and reduced side effects.