  Bibliographic metrics are commonly utilized for evaluation purposes within
academia, often in conjunction with other metrics. These metrics vary widely
across fields and change with the seniority of the scholar; consequently, the
only way to interpret these values is by comparison with other academics within
the same field and of similar seniority. We propose a simple extension that
allows us to create metrics that are easy to interpret and can make comparisons
easier. Our basic idea is to create benchmarks and then utilize percentile
indicators to measure the performance of a scholar or publication over time.
These percentile-based metrics allow for comparison of people and publications
of different seniority and are easily interpretable. Furthermore, we
demonstrate that the rank percentile indicators have reasonable predictive
power. The publication indicator is highly stable over time, while the scholar
indicator exhibits short-term stability and can be predicted via a simple
linear regression model. While more advanced models offer slightly superior
performance, the simplicity and interpretability of the simple model impose
significant advantages over the additional complexity of other models.
