| # Reproduction instructions | |
| ```bash | |
| uv run --with numpy==2.2.6 --with matplotlib==3.10.3 reproduce.py | |
| (git clone https://github.com/mmschlk/shapiq.git vendor_shapiq && cd vendor_shapiq && git checkout 12ec2878fb61b94c01a8c1260a18108eac165538) | |
| # Download dataset-latest.zip from the pinned TALENT revision linked below, | |
| # extract its data/ directory as talent_data/data/, then run: | |
| uv run --python 3.12 --with ./vendor_shapiq --with causal-learn claim56_reproduction.py | |
| (cd results && sha256sum -c SHA256SUMS) | |
| (cd results/claim56_full && sha256sum -c SHA256SUMS) | |
| ``` | |
| The deterministic CPU run uses seed `18355` and fails closed on paper/source | |
| checksum drift. It independently implements the published pseudocode and | |
| produces machine-readable exact-graph, boundary-sampling, identifiability, and | |
| complexity audits. | |
| The named-estimator rerun uses the public shapiq repository pinned above. The | |
| real-data rerun uses the public TALENT release pinned at revision | |
| 7bd276bcb7f6b4c0998025855528bd76bd88f13d: | |
| https://huggingface.co/datasets/LAMDA-Tabular/TALENT/tree/7bd276bcb7f6b4c0998025855528bd76bd88f13d | |
| The 648 paired Claim-5 runs and all 156 Claim-6 dataset rows are preserved in | |
| `results/claim56_full/`. The TALENT archive itself is not duplicated in this | |
| bundle. | |