ArticleForensic science international. Synergy2022
Human and machine similarity judgments in forensic firearm comparisons.
Article in Forensic science international. Synergy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Interpol review of forensic firearm examination, 2022-2025.Forensic science international. Synergy · 2026Review
- An overview of log likelihood ratio cost in forensic science - Where is it used and what values can we expect?Forensic science international. Synergy · 2024Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is unclear whether humans assess similarity differently than automated algorithms in firearms comparisons. Human participants (untrained in firearm examination) were asked to assess the similarity of pairs of images (from 0 to 100). A sample of 40 pairs of cartridge casing 2D-images was used. The images were divided into 4 groups according to their similarity as determined by an algorithm. Humans were able to distinguish between matches and non-matches (both when shown the 2 middle groups, as well as when shown all 4 groups). Thus, humans are able to make high-quality similarity judgments in firearm comparisons based on two images. The humans' similarity scores were superior to the algorithms' scores at distinguishing matches and non-matches, but inferior in assessing similarity within groups. This suggests that humans do not have the same group thresholds as the algorithm, and that a hybrid human-machine approach could provide better identification results than humans or algorithms alone.
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