ReviewForensic science international. Synergy2022
Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science.
Review 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 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- HelixCross - Design and development of an AI-powered cross-examination simulation for forensic expert testimony training.Forensic science international. Synergy · 2026Article
- Nothing new under the sun: The NIST primer on "Probability and Likelihood Ratios" gives a misleading negative portrayal of the likelihood-ratio framework.Forensic science international. Synergy · 2026Article
- Review
- The development of Forensic Science in the criminal justice system of England and Wales (2000-2024): A systematic review.Forensic science international. Synergy · 2025Article
- Article
- 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
- From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation.Forensic science international. Synergy · 2024Article
- The scientific reinvention of forensic science.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The opacity myth: A response to Swofford & Champod (2022).Forensic science international. Synergy · 2022Article
- Forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios.Forensic science international. Synergy · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Widespread practice across the majority of branches of forensic science uses analytical methods based on human perception, and interpretive methods based on subjective judgement. These methods are non-transparent and are susceptible to cognitive bias, interpretation is often logically flawed, and forensic-evaluation systems are often not empirically validated. I describe a paradigm shift in which existing methods are replaced by methods based on relevant data, quantitative measurements, and statistical models; methods that are transparent and reproducible, are intrinsically resistant to cognitive bias, use the logically correct framework for interpretation of evidence (the likelihood-ratio framework), and are empirically validated under casework conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.