Add paper link, GitHub link, task category, and sample usage

Hi! I'm Niels, part of the community science team at Hugging Face. I've updated the dataset card to better document the artifact. This PR includes:
- A link to the associated research paper.
- A link to the official GitHub repository.
- Relevant task category (`text-classification`).
- A sample usage code snippet from the repository's documentation.
- Preservation of the existing dataset metadata (features, splits, and configs).

README.md

@@ -1,5 +1,7 @@
 ---
 license: cc-by-4.0
+task_categories:
+- text-classification
 dataset_version: 0.2.3
 dataset_info:
   features:
@@ -243,10 +245,43 @@ configs:
   - split: test
     path: data/test-*
 ---
-# ds4dh/ct-dosing-errors
+
+# Dataset Card for ct-dosing-errors
+
+This dataset provides the materials accompanying the paper "[Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning](https://huggingface.co/papers/2602.22285)".
+
+The dataset is designed for the prediction of dosing errors in interventional clinical research. It comprises 42,112 clinical trials extracted from ClinicalTrials.gov, containing structured, semi-structured trial data, and unstructured protocol-related free-text data.
+
+## Links
+
+- **Paper:** [https://huggingface.co/papers/2602.22285](https://huggingface.co/papers/2602.22285)
+- **GitHub Repository:** [https://github.com/ds4dh/CT-dosing-errors](https://github.com/ds4dh/CT-dosing-errors)
+
+## Sample Usage
+
+You can load the dataset using the `datasets` library:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset(
+    "ds4dh/ct-dosing-errors",
+    split="train"
+)
+
+print(ds)
+print(ds.features)
+```
+
+## Dataset Summary
+
+The dataset includes labels for the prediction of dosing errors derived from adverse event reports and MedDRA terminology. It features a wide range of fields including:
+- **Textual data:** Brief summaries, detailed descriptions, conditions, and protocol PDF text.
+- **Structured data:** Clinical trial phases, enrollment counts, allocation, and intervention types.
+- **Labels:** Binary indicators (`LABEL_wilson_label`) for elevated dosing error rates.
 
 ## Version
 This repository contains dataset version **0.2.3**.
 
 ## License
-This dataset is licensed under **CC BY 4.0** (`cc-by-4.0`).
+This dataset is licensed under **CC BY 4.0** (`cc-by-4.0`).