The Open Science Protocol.

Upon submission via the unified access gate, manuscripts are immediately decoupled from Author Identifiable Information (AII). The raw text, figures, and datasets are parsed into a multi-dimensional tensor representation using our proprietary Semantic Decomposition Engine.

The document undergoes a stringent 400-point algorithmic pre-screening. This phase is designed to execute topological data analysis on the manuscript's citations, identifying circular dependency rings, predatory journal inclusions, and anomalous statistical reporting (e.g., violations of Benford’s Law in the provided datasets). Furthermore, adversarial neural networks scan the corpus for synthetic generative anomalies, ensuring human-centric authorship provenance.

Traditional assignment relies on the limited professional network of human editors, often introducing geographic and institutional bias. Neural Review mitigates this via an N-dimensional mapping algorithm.

The manuscript's core hypotheses are projected into a global knowledge space, populated by the active research profiles of over 40,000 verified Associate Editors. A proximity calculation determines the top three statistically optimal handlers based on historical publication focus, grant trajectory, and methodological parity. The system prioritizes exact alignment over institutional prestige, minimizing editorial mismatch variance to $ \sigma < 0.05 $.

Unlike standard double-blind reviews, Neural Review operates a Triple-Masked protocol. The Handling Editor, the Peer Reviewers, and the Authors are completely isolated in separate encrypted sub-environments.

• Authors receive aggregated feedback vectors without reviewer institutional markers.
• Reviewers evaluate raw, de-branded text devoid of stylistic fingerprints, thanks to automated formatting homogenization.
• Editors observe consensus scoring grids without access to the specific underlying identities until a final cryptographic commit is executed.

During this phase, all communications and revision logs are cryptographically hashed and appended to an ongoing internal ledger, ensuring that no review coercion or editorial misconduct can proceed unrecorded.

Upon successfully passing the designated consensus threshold, the manuscript is transitioned into its terminal state. The final PDF rendering, the raw supplementary datasets, the peer review audit trail, and the authoritative decision matrix are concatenated into a single Merkle tree.

The root hash of this tree is committed to the Sovereign Registry chain. The resultant Archival Resource Key (ARK) is then syndicated across our 14 globally distributed nodes (ranging from EU-C1 to CA-W1). This ensures that the scientific record is completely impervious to retroactive alteration, political censorship, or institutional retraction without leaving a permanent on-chain forensic footprint.