Evidence map›Paper›PMID 42298825›Full record

ArticleJournal of forensic sciences2026

Global interlaboratory study: Assessing consistency and accuracy for determining source of face, hands, and clothing images across forensic practitioners and laypersons.

Kelly A Meiklejohn, Chau-Wai Wong, Melissa K R Scheible, Yang Qu, Jane Harris, Lora Sims

Abstract read
In one paragraph

Article in Journal of forensic sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kelly A MeiklejohnDepartment of Population Health and Pathobiology, North Carolina State University, College of Veterinary Medicine, Raleigh, North Carolina, USA.ORCID https://orcid.org/0000-0001-6125-2963
Chau-Wai WongDepartment of Electrical and Computer Engineering, North Carolina State University, College of Engineering, Raleigh, North Carolina, USA.
Melissa K R ScheibleDepartment of Population Health and Pathobiology, North Carolina State University, College of Veterinary Medicine, Raleigh, North Carolina, USA.
Yang QuClinical Studies Core, Office of Research, North Carolina State University, College of Veterinary Medicine, Raleigh, North Carolina, USA.
Jane HarrisCenter for Forensic Science, Northern Michigan University, Marquette, Michigan, USA.
Lora SimsFace Center of Excellence (FaCE), Ideal Innovations, Inc., Arlington, Virginia, USA.

Funding

NIST DOC 70NANB23H275
6 · The paper itself

Abstract

Images containing faces, body parts, vehicles, weapons, clothing, luggage, furniture, landscapes, and buildings are routinely sent to forensic laboratories for comparison. Trained forensic practitioners offer an opinion regarding a common source or a different source. Results from comparisons are typically reported using opinion categories, and the number used can vary (typically 3-7 categories). To harmonize opinion categories used across digital multimedia disciplines, the Organization of Scientific Area Committees (OSAC) for Forensic Science developed OSAC Proposed Standard 2022-S-0001 (Standard Guide for Image Comparison Opinions), which details five opinion categories for determining image source. To ensure this standard meets the OSAC program goal of developing technically sound standards, an interlaboratory study focused on 2022-S-0001 was conducted. Combining machine learning and input from subject matter experts, 20 pairs of face, hands, and clothing images were selected for use that represented varying sources and difficulty. Qualtrics was used to disseminate a survey and collect responses from forensic practitioners (n = 38) and laypersons (n = 44). For all three image subject categories, statistically higher agreement (selection of the same opinion source category for the same pair of images) was observed between practitioners over laypersons. Practitioners were statistically more accurate at determining the true source over laypersons for face (p = 0.005) and hand (p = 0.043) image pairs. This study highlighted that when individuals are provided with a clear and detailed framework of source opinion categories, moderate agreement and high accuracy (especially for practitioners) can be achieved for face, hand, and clothing image comparisons.

Indexed as

ClothingFaceForensic SciencesHandPhotographyForensic ImagingHumansMachine LearningObserver VariationReproducibility of Resultsclothing comparisondigital multimediafacial comparisonhand comparisonimage comparisonsopinion categoriesOSAC proposed standard

Identifiers

PMID42298825
PMCPMC13534925

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.