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Orchestration for bibliometrics, topological network analysis, and hypothesis scoring.
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Core inference logic, prompt construction, and RDF/Nanopublication serialization.
Operations for federated API querying across OpenAlex, Semantic Scholar, and arXiv.
Tooling for injecting JSON/CSV statistics into Markdown evaluation templates.
Core orchestration guidelines and MCP interactions for the src/ library.
Orchestrates matplotlib and seaborn pipelines for rendering figures.
Based on SOC occupation classification
| name | Statistical & Metric Analysis |
| description | Orchestration for bibliometrics, topological network analysis, and hypothesis scoring. |
You are interacting with the src/analysis/ module of the Meta-Analysis project. This layer transforms raw literature and structured knowledge graph edges into quantifiable metrics.
random_seed=42 across any clustering, layout algorithms (e.g. UMAP/t-SNE if added), or network metrics (Louvain community detection) to ensure reproducible builds.