Preprint / scholarly article
Layered Online Service and Replay Control for Verified AI R and D Acceleration
- Published
- DOI
- 10.5281/zenodo.19836225
Abstract
This preprint introduces Layered Online Service and Certified Replay Control (LOSCR), a model-independent framework for evaluating and controlling verified acceleration in AI-assisted R&D. It separates lightweight telemetry from stronger evidence claims and combines service-capacity control, certified replay, machine-readable claim profiles, deterministic checking, append-only ledgers, evaluator audits, and falsification rules so acceleration claims can be checked, downgraded, quarantined, or escalated against observable evidence and operational capacity.
Keywords
- Artificial intelligence
- AI R&D acceleration
- AI-assisted research
- AI agents
- online control
- service capacity
- certified replay
- reproducible AI workflows
- evaluation methodology
- evaluator audits
- benchmark contamination
- validation throughput
- research automation
- software engineering automation
- Machine learning
- work-in-process
- claim verification
- reusable artifacts
- AI governance
- operational reliability