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wsdm-reproducibility

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Use when hardening the reproducibility of a WSDM paper built on logs, graphs, or user-interaction data - provenance of behavioral datasets, temporal split discipline, click-bias assumptions, seed and variance reporting, privacy-preserving release, and honesty tiers for results no outsider can rerun.

When to use

• hardening reproducibility of WSDM papers
• provenance of behavioral datasets
• temporal split discipline
• click-bias assumptions
• seed and variance reporting
• privacy-preserving release
• honesty tiers for results
• pre-submission reproducibility sweep

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