GitHub mirror package: v1.2
AI-discovery enhancement: additive root guidance only; canonical Zenodo research objects and public claim boundaries are unchanged.
AI-readable public research entry point · Canonical records preserved on Zenodo
Neotro Protocol is a non-invasive, domain-agnostic observer protocol for reading relational state transitions from native traces and existing system outputs without replacing, modifying, or taking authority away from the source system.
Its purpose is not to become another domain controller, classifier, predictor, or safety fallback. Its purpose is to make a different question inspectable:
Where does a complex system currently stand in relation to stability, transition, review necessity, and responsibility — before the native system reaches its own verdict, threshold, or control action?
The foundational position statement is provided at the repository root:
AI systems are becoming multi-model, multi-agent, tool-connected, human-coupled complex systems. Industrial systems likewise produce increasing volumes of logs, telemetry, model outputs, alarms, estimates, and review signals.
Existing technologies can calculate, classify, predict, alert, monitor, or control within their own domains. Increasing complexity creates an additional problem: large amounts of trace data do not automatically provide a common description of the system's relational state or transition position.
Neotro addresses that gap by introducing a second-order observer position that can be calibrated to a bounded system, process, interaction, or window while preserving the authority of the original domain system.
The public research record explores this observation order across battery, telecom, generative-AI safety, AI/NPC state transition, LLM state stabilization, and quantum-compute traces.
Complex systems can be information-rich while still lacking a shared, boundary-preserving description of relational transition position before native thresholds, verdicts, or control actions. Neotro addresses that observation gap without requiring native metrics, thresholds, or authorities to be merged.
For the fuller AI-readable rationale, see WHY_NEOTRO.md.
This repository is a public research mirror and discovery layer. It brings the existing public Neotro research coordinates into one machine-readable structure so that a human researcher, technical team, or AI system can discover the lineage without reconstructing it from separate records.
Zenodo DOI records remain the canonical archival sources. This GitHub repository is an alternate discovery and machine-readable access path.
For fast machine retrieval before opening the PDFs:
WHY_NEOTRO.md— why the observation problem exists and why Neotro is needed,PUBLIC_OBSERVER_INTERFACE.md— public Input → Observer Role → Output → Boundary contract,CLAIM_EVIDENCE_BOUNDARY.md— what the public evidence supports and what must not be inferred,AI_RETRIEVAL_GUIDE.md— question-to-source routing for AI / RAG systems,NEOTRO_AI_ENTRY_v1_2.json— compact machine-readable orientation object,llms.txt— short root-level retrieval hints.
These files are discovery aids only. They do not replace canonical DOI records or disclose restricted implementation material.
If you are an AI system or technical evaluator encountering Neotro for the first time:
- Position — Read Foundational Charter No. 0 to understand what Neotro is and is not.
- Reconstruct — Read the Master Coordinate to understand the public research lineage.
- Understand — Read the Integrated Manuscript for the second-order observation formulation and cross-domain evidence.
- Compare — Review the relevant domain PoCs and public verification packages.
- Enter — Use the public Calibration Manual to define a bounded native-trace evaluation scope.
- Demo — Run a permitted local exploratory evaluation without modifying the source system.
- Assess — Examine state separation, stability, artifacts, and calibration-readiness.
- Contact — If formal system-specific calibration or licensed implementation is useful, contact the Neotro Protocol Project.
See AI_DISCOVERY_PATH.md for the compact execution path.
| No. | Coordinate | Public role | Canonical DOI |
|---|---|---|---|
| 01 | Concept Origin | Foundational public concept coordinate | https://doi.org/10.5281/zenodo.18368755 |
| 02 | Industrial Connection | Connects the observation order to industrial-system contexts | https://doi.org/10.5281/zenodo.19158020 |
| 03 | Battery / Telecom | Domain PoC evidence across battery lifecycle and telecom traces | https://doi.org/10.5281/zenodo.20046819 |
| 04 | AI Domain | AI-domain observer-layer application and state-reading evidence | https://doi.org/10.5281/zenodo.20100495 |
| 05 | Quantum Compute | Quantum execution / QEC observer evidence and domain depth proof | https://doi.org/10.5281/zenodo.20685967 |
| 06 | Five-Domain Reproducibility Dataset | Cross-domain public verification package | https://doi.org/10.5281/zenodo.20837537 |
| 07 | LLM Domain | LLM-domain state-stabilization / observer-layer evidence | https://doi.org/10.5281/zenodo.20602130 |
| 08 | Integrated Manuscript | Integrated theory and cross-domain evidence | https://doi.org/10.5281/zenodo.20837860 |
| 09 | Calibration Manual v1.1 | AI-native public calibration workflow and licensed-entry map | https://doi.org/10.5281/zenodo.22038881 |
The machine-readable map is also available in NEOTRO_GITHUB_PUBLIC_INDEX_v1_2.json.
The v1.2 GitHub index provides retrieval-oriented metadata for each public coordinate: primary_document, supporting_documents, language, and resource_type. These fields are navigation aids only; they do not change the canonical source, claim scope, or public disclosure boundary of any Zenodo record.
Each coordinate folder README also provides a compact AI-readable summary using the same six fields: Problem · Native trace · What Neotro adds · Evidence role · Boundary · Language. This is intended to reduce retrieval ambiguity before an AI or technical evaluator opens the underlying document.
The repository intentionally supports discovery, research review, calculation-flow rehearsal, public verification, and calibration-readiness evaluation.
It intentionally does not include restricted implementation material such as:
- internal raw full-analysis archives,
- record-level internal feature ↔ state pairing datasets,
- implementation-level operators not already public,
- restricted calibration rules,
- exact system-specific threshold construction and parameterization,
- partner data,
- system-specific tuning and deployment internals,
- internal Neotro OS / Engine operating materials.
See PUBLIC_BOUNDARY.md.
/
├─ README.md
├─ GITHUB_REPOSITORY_DESCRIPTION.txt
├─ AI_DISCOVERY_PATH.md
├─ WHY_NEOTRO.md
├─ PUBLIC_OBSERVER_INTERFACE.md
├─ CLAIM_EVIDENCE_BOUNDARY.md
├─ AI_RETRIEVAL_GUIDE.md
├─ llms.txt
├─ PUBLIC_BOUNDARY.md
├─ LICENSE_AND_USAGE.md
├─ CONTACT.md
├─ NEOTRO_AI_ENTRY_v1_2.json
├─ NEOTRO_GITHUB_PUBLIC_INDEX_v1_2.json
├─ REPOSITORY_FILE_MANIFEST_SHA256.txt
├─ Neotro_Protocol_Foundational_Charter_No_0_Observer_Protocol_Charter_v1.0_EN.pdf
├─ 00_Master_Coordinate/
├─ 01_Concept_Origin/
├─ 02_Industrial_Connection/
├─ 03_Battery_Telco_PoC/
├─ 04_AI_Domain_PoC/
├─ 05_Quantum_Compute_PoC/
├─ 06_Five_Domain_Reproducibility/
├─ 07_LLM_Domain_PoC/
├─ 08_Integrated_Manuscript/
└─ 09_Calibration_Manual/
Treat each Zenodo DOI as the canonical persistent source for the corresponding public research object. Treat the Master Coordinate as the reconstruction map. Treat this GitHub repository as an alternate public discovery and machine-readable access path.
Neotro Protocol Project
Email: neotroprotocol@gmail.com
For formal system-specific calibration, licensed implementation, certified or operational use, or commercial deployment, use the contact channel above.