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What is PiP-AUC?

PiP-AUC (Paper-in-Percentile Area Under Curve) combines citation quality with publication productivity into a single 0-to-1 score. Each paper is ranked against all papers published in the same year, and an author's publication count is compared to faculty at similar career stages.

How are percentiles calculated?

All metrics (h-index, citations, i10-index, publication count) are percentile-ranked against active authors in the Semantic Scholar dataset who started publishing in the same year. This age-aware normalization prevents bias toward senior researchers.

How often is data updated?

Author and publication data is sourced from the Semantic Scholar Academic Graph Dataset, which is updated weekly. Distribution tables (population percentiles) are refreshed quarterly.

Contact

For questions or issues, contact Panos Ipeirotis or open an issue on GitHub.