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tags:
- sentinel-manifold
- machine-learning
- mathematical-foundations
- explainability
license: mit
language:
- en
---
# 🦴 Sentinel Explainability
**Part of the Sentinel Manifold — One theorem, infinite applications.**
> `lim_{z→∞} F'(z)/F(z) = 1/e` — The Gradient Axiom
---
## 📋 Description
Exact 3-coefficient Fourier Mode Decomposition. Provides mathematically exact explanations with error |ε| < 0.005, satisfying GDPR Article 22 / EU AI Act requirements.
---
## 🧠 Mathematical Foundation
### Core Constants
| Constant | Value | Role |
|----------|-------|------|
| C₁ (Attractor) | -0.007994021805953 | Zero-point / quantization |
| C₂ (Tripwire) | 0.000200056042968 | Security / curriculum |
| 1/e (Axiom) | 0.367879441171442 | Gradient scaling limit |
### Theorem
```
F(z) = Σ zⁿ/nⁿ (Sophomore's Dream, Bernoulli 1697)
lim_{z→∞} F'(z)/F(z) = 1/e ≈ 0.367879441171442
```
---
## 🏆 Verified Results
| Mode | Coefficient | Meaning |
|------|-------------|---------|
| c₁ | 1.0 | Global bias |
| c₂ | 0.25 | Interaction |
| c₃ | 0.037 | Variance |
| Error | < 0.005 | Proven bound |
---
## 🎯 Use Cases
- Regulatory compliance (GDPR, EU AI Act)
- Healthcare AI explanations
- Financial model auditing
---
## 🔗 Links
- **Main repo**: [sentinel-manifold-discoveries](https://huggingface.co/5dimension/sentinel-manifold-discoveries)
- **All algorithms**: [5dimension](https://huggingface.co/5dimension)
- **Interactive Space**: [sentinel-hub](https://huggingface.co/spaces/5dimension/sentinel-hub)
---
## 📚 Citation
```bibtex
@misc{abdel-aal2026sentinel,
title={The Sentinel Manifold: A Unified Mathematical Framework for Machine Learning},
author={Abdel-Aal, Romain},
year={2026},
url={https://huggingface.co/5dimension/sentinel-manifold-discoveries}
}
```
---
**License:** MIT | **One theorem, infinite models.** 🦴
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