license: mit
language:
- en
tags:
- dslo
- v0.7 release cluster
- structured ingestion
- semantic substrate
- multi-manifold geometry
- scientific metadata
- thermodynamic drift
DSLO v0.7 — Semantic Substrate Specification (Machine-Facing Mirror)
This dataset provides the machine-facing mirror of the DSLO v0.7 Semantic Substrate Specification. It exposes the structured geometry primitives, legality invariants, cross-surface bindings, and substrate-level metadata used across the DSLO v0.7 release cluster. The canonical, citable artifacts remain the DOI-minted Zenodo records; this dataset serves strictly as an ingestion mirror for computational systems, tooling, and automated reasoning workflows.
Referenced DSLO v0.7 Artifacts (Canonical DOIs)
DSLO v0.7 — Geometry Layer (Thermodynamic Drift)
DOI: 10.5281/zenodo.21864007DSLO v0.7 — Operational Manual (Substrate Architecture)
DOI: 10.5281/zenodo.21864226DSLO v0.7 — Geometry Examples (Drift, Collapse, Recovery)
DOI: 10.5281/zenodo.21864440DSLO v0.7 — Semantic Substrate Metadata Record
DOI: 10.5281/zenodo.21865818
Purpose of This Mirror
The DSLO v0.7 Semantic Substrate Specification is mirrored on Hugging Face to support machine ingestion, structured analysis, and downstream tooling. This mirror provides a model-friendly representation of the v0.7 substrate logic, enabling computational systems to interact with DSLO’s geometry primitives, legality invariants, and cross-surface bindings. All canonical citations must reference the DOI-minted Zenodo artifacts; this dataset is a convenience mirror for machine-facing workflows.
Dataset Structure
/spec/ — substrate-level geometry primitives /surfaces/ — cross-surface bindings /invariants/ — legality-plane and collapse-safety invariants /examples/ — machine-facing examples aligned with v0.7 /metadata/ — structured metadata for ingestion engines
Each directory mirrors the structure of the GitHub repository to ensure consistency across ingestion surfaces.
Metadata
- Version: v0.7
- Release Date: 2026-08-010
- Canonical DOI: 10.5281/zenodo.21865818
- License: MIT
- Homepage: https://www.tnopsi.com
- Source Repository: https://github.com/DSLO/DSLO-v0.7-Semantic-Substrate-Specification
- Mirror: Hugging Face dataset for machine ingestion
DSLO v0.7 Release Cluster Recap
DSLO v0.7 establishes a unified, lawful multi-manifold geometry that advances the discipline across its thermodynamic, operational, and cross-domain surfaces. The Geometry Layer formalizes drift, load, synthetic pressure, collapse thresholds, recovery attractors, and lawful manifold transitions as curvature-based primitives that apply consistently across biological, cultural, abstract, physical, and machine-facing systems.
The Operational Manual defines the invariant-preserving procedures for constructing, validating, and documenting DSLO surfaces, including architecture rules, operator binding constraints, legality-plane verification, runtime-cycle sequencing, and collapse-safety requirements.
The Geometry Examples demonstrate how DSLO invariants manifest across diverse substrates—mimicry, distributed non-neural intelligence, cultural signal encoding, natural optimization, abstract partitioning, and engineered systems—showing how local geometric behavior reflects global substrate laws.
The Semantic Substrate Specification mirrored here provides the structured, machine-ingestible representation of the v0.7 substrate logic, enabling computational systems to interact with DSLO’s scientific surfaces in a model-friendly format.
Together, these artifacts form a coherent v0.7 release cluster that establishes DSLO’s substrate-level geometry and enables lawful traversal, unified thermodynamic modeling, and cross-domain stability analysis for human–machine systems.
Keywords
dslo, semantic substrate, multi-manifold geometry, legality invariants, thermodynamic drift, collapse-safety, machine-facing substrate, scientific metadata, v0.7 release cluster, structured ingestion
Referenced DSLO v0.7 Artifacts
DOI Set — Substrate‑Skin (A0, A4, A5, A6, B1, F2)