
Citation counts often follow a power-law distribution. To prevent single outlier papers from skewing the entire dataset, we apply a Log₁₀ transformation. This ensures that rankings reflect consistent high-quality research rather than viral anomalies.
Unlike simple counting, our engine employs a multi-factor verification system. We cross-reference DOIs against University affiliations to ensure that "Volume" represents distinct, validated scientific contributions.
We recognize that not all authors contribute equally. Our algorithm parses the Author List Order to assign weighted credit (e.g., First Author vs. Principal Investigator), ensuring credit is given where it is scientifically due.