| { |
| "name": "coauthor-physics", |
| "sources": [ |
| { |
| "url": "https://raw.githubusercontent.com/shchur/gnn-benchmark/master/data/npz/ms_academic_phy.npz", |
| "final_url": "https://raw.githubusercontent.com/shchur/gnn-benchmark/master/data/npz/ms_academic_phy.npz", |
| "filename": "ms_academic_phy.npz", |
| "bytes": 16374005, |
| "sha256": "e4d68468eba5fb8f6b280ffd406bd53e6e4295ba1dd2967d6fe99b978e4b3375", |
| "downloaded_at": "2026-07-23T02:14:50+00:00" |
| } |
| ], |
| "conversion": { |
| "script": "convert_npz.py", |
| "label_column": "field", |
| "notes": "shchur gnn-benchmark npz; CSR adjacency symmetrized. Feature matrix too large for CSV (skipped; available in source npz).", |
| "parquet": true, |
| "parquet_notes": "nodes.parquet includes the full feature matrix omitted from nodes.csv for size." |
| }, |
| "graphs": { |
| "default": { |
| "nodes": 34493, |
| "edges": 247962, |
| "label_column": "field", |
| "classes": 5, |
| "class_counts": { |
| "2": 17426, |
| "0": 5750, |
| "1": 5045, |
| "4": 3519, |
| "3": 2753 |
| }, |
| "isolated_nodes": 0, |
| "feature_columns": 0 |
| } |
| }, |
| "title": "Coauthor Physics", |
| "band": "medium", |
| "label_type": "semantic", |
| "task": "Research-field classification (co-authorship)", |
| "license": "MIT (shchur packaging)", |
| "citation": "Shchur et al. Pitfalls of GNN Evaluation. 2018.", |
| "links": [ |
| "https://github.com/shchur/gnn-benchmark" |
| ] |
| } |
|
|
