Interpreting Performance Metrics in Semi-Automated Shark Photo-Identification: Applying IDENTIFIN to Bronze Whaler Shark (Carcharhinus brachyurus, Günther 1870) and White Shark (Carcharodon carcharias, Linnaeus 1758)

Monitoring large elasmobranchs can employ standardized photo-identification protocols to manage diverse and progressively expanding photographic datasets. This study examines the interpretation of performance metrics generated by a dorsal fin–based photo-identification protocol implemented using the semi-automated IDENTIFIN software. The protocol was applied to dorsal fin photographs of bronze whaler shark collected along the South African coast between 2024 and 2025, facilitating the creation of a structured, individual-specific database. Archival photographic data of white shark (2012–2019) served as a methodological reference, providing context for software outputs under different dataset conditions. Analyses focused on the behavior of similarity scores associated with validated matches and on their relationship with image ranking position, a common metric for assessing software performance. Results indicate that similarity scores exhibit comparable distributions across species-specific datasets, supporting their potential use as an operationally complementary metric for interpreting IDENTIFIN outputs. While operator-based visual validation remains essential, this study provides preliminary methodological insights into the interpretation of similarity scores as supportive information within the individual identification process.