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README.md

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-license: cc-by-nc-nd-4.0
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+---
+license: cc-by-nc-nd-4.0
+---
+
+# Dataset Card for ToxiCore
+
+This dataset card provides documentation for the **ToxiCore** dataset, designed to support the development of AI models in toxicology, including toxin detection and antidote recommendation systems.
+
+## Dataset Details
+
+### Dataset Description
+
+**ToxiCore** is a structured dataset containing data on toxic compounds, including their chemical characteristics, associated symptoms, and known treatments or antidotes. It is intended to help train and evaluate machine learning models capable of identifying toxic agents and recommending countermeasures. This dataset is particularly useful in healthcare, emergency response, and pharmacological research.
+
+- **Curated by:** Hayden Banz
+- **Funded by [optional]:** *More Information Needed*
+- **Shared by [optional]:** Hayden Banz
+- **Language(s):** English
+- **License:** CC BY-NC-ND 4.0
+
+### Dataset Sources
+
+- **Repository:** [https://huggingface.co/datasets/haydenbanz/ToxiCore](https://huggingface.co/datasets/haydenbanz/ToxiCore)
+- **Paper [optional]:** *More Information Needed*
+- **Demo [optional]:** *More Information Needed*
+
+## Uses
+
+### Direct Use
+
+This dataset is suitable for:
+
+- Machine learning research in toxicology
+- Building antidote recommendation systems
+- Educational purposes in pharmacology and healthcare AI
+
+### Out-of-Scope Use
+
+This dataset is **not** intended for:
+
+- Real-time diagnosis or treatment in medical settings without professional validation
+- Use in commercial or clinical tools without regulatory approval
+- Any application involving personal or sensitive health data processing
+
+## Dataset Structure
+
+The dataset includes fields such as:
+
+- `compound_name`
+- `toxicity_level`
+- `chemical_properties`
+- `symptoms`
+- `recommended_antidote`
+
+More detailed structure and formatting information can be found in the dataset repository.
+
+## Dataset Creation
+
+### Curation Rationale
+
+This dataset was created to provide a resource for research in AI-based toxicology systems, with a focus on public health applications and academic study.
+
+### Source Data
+
+#### Data Collection and Processing
+
+Data was collected from publicly available scientific literature and verified toxicology resources. Processing steps included cleaning, normalization, and categorization of compound-related data.
+
+#### Who are the source data producers?
+
+The original data comes from medical toxicology literature, chemical safety databases, and government or public health publications.
+
+### Annotations [optional]
+
+#### Annotation Process
+
+Annotations (e.g., symptom tagging, antidote mapping) were manually verified based on referenced sources.
+
+#### Who are the annotators?
+
+The dataset was reviewed and annotated by the curator, Hayden Banz, with assistance from open-source contributors.
+
+#### Personal and Sensitive Information
+
+The dataset does **not** contain personal, sensitive, or private information.
+
+## Bias, Risks, and Limitations
+
+While ToxiCore provides a valuable base for research, it may not include rare toxins, region-specific compounds, or all possible antidotes. Use with caution in high-stakes scenarios.
+
+### Recommendations
+
+This dataset should be used in conjunction with expert guidance and clinical validation. It is recommended for academic, research, and non-commercial experimentation.
+
+## Citation [optional]
+
+**BibTeX:**
+
+```bibtex
+@misc{toxicore2025,
+  author = {Hayden Banz},
+  title = {ToxiCore: Dataset for Toxin Detection and Antidote Recommendation},
+  year = {2025},
+  howpublished = {\url{https://huggingface.co/datasets/haydenbanz/ToxiCore}},
+}