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Phase-Based Neural Embeddings
Semantic Scalpel is a phase-based neural embedding system using complex-valued phase-rotation embeddings to achieve 97.1% certified accuracy (by tier: T1 100%, T2 100%, T3 75%, T4 100%) with 9,962,112 parameters. It delivers 12.61ms average latency at 165 predictions/second throughput. Specialized in metonymy detection, coercion analysis, and garden-path sentence disambiguation. Exports to ONNX and TorchScript with INT8/FP16 quantization support. Integrates with LangChain, LlamaIndex, and HuggingFace, and provides an MCP server for AI agent tool access.
Five-paper series establishing stagnation dynamics as the dominant predictor of optimization outcomes with a universal three-regime structure.
A 72,264-parameter pure Python neural network trained across 18 scientific domains using spectral mathematics from the Unity Lang project.