C. Navarro-Martinez

This study develops a machine learning approach to classify felid calls and identify distinguishing acoustic features, achieving 91% accuracy for call type and 86% for species classification within Pantherinae.

This paper introduces a method to assess significant correlations between pairs of traits across all most parsimonious evolutionary reconstructions using a phylogenetic tree.