SKILL.md
H-Index and Research Impact Metrics Guide
Understand, calculate, and responsibly interpret bibliometric indicators including h-index, impact factor, and related metrics.
Core Bibliometric Indicators
H-Index
The h-index (Hirsch index) is defined as: a researcher has an h-index of h if h of their papers have each been cited at least h times.
Example: If a researcher has published 20 papers with citation counts [120, 80, 55, 40, 22, 18, 15, 12, 10, 8, 5, 3, 2, 2, 1, 1, 0, 0, 0, 0], their h-index is 10 (10 papers with at least 10 citations each).
def calculate_h_index(citation_counts):
"""Calculate h-index from a list of citation counts."""
sorted_counts = sorted(citation_counts, reverse=True)
h = 0
for i, count in enumerate(sorted_counts):
if count >= i + 1:
h = i + 1
else:
break
return h
# Example
citations = [120, 80, 55, 40, 22, 18, 15, 12, 10, 8, 5, 3, 2, 2, 1, 1, 0, 0, 0, 0]
print(f"h-index: {calculate_h_index(citations)}") # Output: 10
Related Author-Level Metrics
| Metric | Definition | Advantage |
|---|---|---|
| h-index | h papers with >= h citations | Simple, robust to outliers |
| i10-index | Number of papers with >= 10 citations | Intuitive threshold (Google Scholar uses this) |
| g-index | Largest g such that top g papers have >= g^2 total citations | Rewards highly cited papers more |
| m-quotient | h-index divided by years since first publication | Normalizes for career length |
| hI-norm | h-index divided by average number of co-authors | Adjusts for team size |
