arXiv (All)
open access
CompProv Produces Machine Readable Graphs Encoding Microscopic Algebraic Provenance for Reproducible Computation
The reliability of computational results in scientific research and financial modeling increasingly depends on verifiable traceability, not merely on trust in a reported output. Existing provenance systems operate at the granularity of files, datasets, or pipeline stages, leaving the internal sequen
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- CompProv Produces Machine Readable Graphs Encoding Microscopic Algebraic Provenance for Reproducible Computation#1169622
- Fusion of computational and experimental provenance in RO-Crate.#625918
- Structured Schemas for Provenance-Rich, LLM-Assisted QSP Model Calibration.#420968
- Quantitative Performance Modeling of Scientific Computations#464633
- Commercial Deployment of High-Assurance Financial Networks: Five Physical-Layer Provenance Pillars and a Zero-Friction Integration Architecture#282428
Record · ID 1156475
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive