---
license: mit
task_categories:
- text-generation
- fill-mask
language:
- en
tags:
- stem
- science
- math
- physics
- biology
- education
pretty_name: Palladium STEM Preview
size_categories:
- 10K<n<100K
---

# ⚛️ Palladium-STEM (Preview): High-Density Scientific Corpus

> **"The Top 0.17% of the Open Web."**

## Overview
This dataset is a **25,000-document preview** of the upcoming **Palladium-V2 STEM Corpus**. It represents the "Platinum Tier" survivors from a pool of **14.8 million scanned documents**, selected for high information density, academic rigor, and reasoning capability.

## The "Goldilocks" Methodology
Unlike standard web scrapes, this data was processed using a custom GPU-accelerated refinery:
1.  **CPU Gatekeeper:** Filters for academic structure, citations, and mathematical notation (LaTeX, proofs, algorithms).
2.  **GPU Classifier:** A BERT-based educational model scores every document on pedagogical quality.
3.  **The Result:** A **0.17% yield rate**. We rejected 99.83% of the content to leave only high-grade signal.

## Data Provenance
* **Sources:** High-authority domains including `phys.org`, `wikipedia.org`, `newscientist.com`, `betterlesson.com`, and university domains (`.edu`).
* **Content:** Hard sciences (Physics, Chemistry), Mathematics (Proofs, Logic), Computer Science (Algorithms), and Academic Curriculum.
* **Quality:** Average educational score of **3.78 / 5.0** (vs. standard web average of <1.5).

## Usage
This preview is intended for:
* Pre-training LLMs on high-quality reasoning data.
* Fine-tuning models for STEM tasks.
* Evaluating data quality filters.

## Full Dataset (Coming Soon)
The full Palladium-V2 corpus (targeting 5M+ documents / 5B+ tokens) is currently mining. 
**[Contact us for early access]**