Vol. 26 No. 3 (2026): Machine Learning in Paleontology: from data to insights

PE-APA is proud to present the first thematic volume dedicated to Machine Learning in Paleontology published by a paleontological journal, positioning PE-APA at the forefront of this rapidly developing field. The volume will feature research applying supervised and unsupervised learning to paleontological data, including taxonomic recognition, shape analysis, body-mass prediction, and methodological approaches. By bringing together innovative, reproducible data-science applications, this volume aims to showcase the potential of machine learning to address emerging questions in paleontology. It also represents a starting point for future thematic volumes exploring artificial intelligence and its applications in paleontological research.