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This Wiki home page is designed to look like a high-end research portal. It uses clean Markdown architecture, clinical-grade terminology, and visual signposting to position GenZERO as a sophisticated "Frontier AI" project.

🌐 GenZERO Wiki: Central Knowledge Base Pathway GenAI Hackathon 2025 | Track C: Frontier AI Welcome to the official technical documentation for GenZERO, a tri-modular neuro-architectural framework designed to decode the complex relationship between adolescent physiology and mental health.

💎 The GenZERO Philosophy"Standard LLMs treat human behavior as text. GenZERO treats behavior as a dynamic, spiking biological signal."Traditional models suffer from Temporal Loss (forgetting the "rhythm" of movement) and Polysemanticity (the "Black Box" problem). GenZERO solves this by using Pathway's BDH architecture to create a real-time digital twin of a patient's neuro-behavioral state.🛠️ The Tri-Modular Core (At a Glance)⚡ Module I: The Synaptic Processor (BDH)Role: Real-time ingestion of 5Hz actigraphy.Innovation: Replaces standard Backpropagation with Online Hebbian Learning.Metric: $O(T)$ Linear Efficiency.🔍 Module II: The Semantic Filter (SAE)Role: Translating "Neural Noise" into "Clinical Insight."Innovation: Disentangles 4,096 dimensions into 15 Monosemantic Features.Outcome: Clinicians can identify specific triggers like Circadian Drift or Social Withdrawal Jitter.📈 Module III: The Decision Manifold (Hybrid Ensemble)Role: Final diagnostic classification ($sii$ & $PCIAT$).Innovation: Merges Neural Embeddings with Gradient Boosted Decision Trees (XGBoost/LightGBM).Outcome: Superior performance on tabular-heavy clinical datasets.📉 Live Performance BenchmarkCurrent State: v1.0.4-RefinedPrimary Target: PCIAT (Internet Addiction Index)

🤝 Contributing & Community GenZERO is an open-science initiative. If you are a neuroscientist, ML engineer, or clinical researcher, we invite you to explore our Repository