Citation Analysis

Bayesian Portfolio Optimization\\ by Predictive Synthesis
Masahiro Kato, Kentaro Baba, Hibiki Kaibuchi, Ryo Inokuchi
https://arxiv.org/abs/2510.07180
32
Citation mentions
18
Cited references
6
Sections
3,356
Words (approx)

References by Citation Intensity

Ordered by composite index (descending). Higher values indicate more intensive citation.

# Reference Year Mentions Breadth Sec. Wtd Share Composite Main %
1 5 4 8.0 0.156 1.000 100%
2 3 2 4.0 0.094 0.737 100%
3 3 2 5.0 0.094 0.737 100%
4 4 1 8.0 0.125 0.644 100%
5 2 1 4.0 0.062 0.511 100%
6 2 1 4.0 0.062 0.511 100%
7 2 1 4.0 0.062 0.511 100%
8 1 1 1.0 0.031 0.406 100%
9 1 1 1.0 0.031 0.406 100%
10 1 1 1.0 0.031 0.406 100%
11 1 1 1.0 0.031 0.406 100%
12 1 1 1.0 0.031 0.406 100%
13 1 1 2.0 0.031 0.406 100%
14 1 1 2.0 0.031 0.406 100%
15 1 1 2.0 0.031 0.406 100%
16 1 1 2.0 0.031 0.406 100%
17 1 1 2.0 0.031 0.406 100%
18 1 1 2.0 0.031 0.406 100%
Measures: Mentions = total in-text citations; Breadth = distinct sections; Sec. Wtd = section-weighted count (body ×2, lit review/appendix ×0.5); Share = mentions / total citations in paper; Composite = geometric mean of normalised count, breadth, and main-text ratio; Main % = fraction of mentions in main text (excl. appendix). (self) = self-citation.