JKNT Minimal Reference Template (Frozen Baseline Implementation)

This record provides a frozen, minimal reference implementation for the JKNT system. The software implements a deterministic mapping of integer indices onto the unit sphere using: Weyl/Kronecker equidistributed longitude, Archimedean equal-area latitude, fixed sexagesimal (base-60) symbol quantization. The purpose of this release is to serve as a baseline for auditing, reproducibility, and teaching, not as a feature-complete system. The implementation deliberately avoids extensions, optimizations, heuristics, adaptive behavior, or external dependencies beyond standard scientific Python libraries. All outputs are deterministic given identical inputs. No network access, randomness, or hidden state is used. A SHA-256 manifest is generated for all emitted files to support independent verification and archival integrity. This baseline is released under the MIT License and is intended to remain unchanged. Future JKNT-related work, experiments, or applications should reference this record as the stable baseline implementation. This record provides a frozen, minimal reference implementation for the JKNT system and is published as a defensive prior-art baseline. The software implements a deterministic mapping of integer indices onto the unit sphere using: Weyl/Kronecker equidistributed longitude, Archimedean equal-area latitude, fixed sexagesimal (base-60) symbol quantization. The purpose of this release is to serve as a stable baseline for auditing, reproducibility, education, and accessibility, not as a feature-complete or optimized system. The implementation deliberately avoids extensions, adaptive logic, heuristics, machine learning, or external network dependencies. All outputs are fully deterministic given identical inputs. No randomness, telemetry, or hidden state is used. A SHA-256 manifest is generated for all emitted files to enable independent verification, reproducibility, and long-term archival integrity. Accessibility and Universal Design for Learning (UDL) This baseline is designed to support Universal Design for Learning (UDL) principles: deterministic, inspectable outputs suitable for screen readers and assistive technologies, plain-text and CSV data formats compatible with accessible tooling, minimal cognitive load through a deliberately constrained and auditable design, offline execution to ensure equitable access in restricted or low-connectivity environments. The implementation is suitable for instructional, demonstrative, and assistive use in educational and research contexts, including environments requiring accessibility accommodations. Prior-Art and Defensive Publication Notice This record is intentionally published to establish prior art for the described deterministic mapping, symbol quantization, and baseline validation approach. The scope of this release is limited to a minimal reference implementation; it makes no claims regarding extensions, applications, or optimizations beyond the explicitly defined baseline. The software is released under the MIT License and is intended to remain unchanged. Future JKNT-related work, research, or applications should reference this record as the canonical baseline implementation.