Vink M, Sjerps M J
University of Amsterdam, KdVI, PO Box 94248, 1090 GE, Amsterdam, Netherlands.
Netherlands Forensic Institute, Laan van Ypenburg 6, 2497GB, The Hague, Netherlands.
Forensic Sci Int Synerg. 2023 May 12;6:100331. doi: 10.1016/j.fsisyn.2023.100331. eCollection 2023.
This paper presents a collection of idioms that is useful for modeling activity level evaluations in forensic science using Bayesian networks. The idioms are categorized into five groups: cause-consequence idioms, narrative idioms, synthesis idioms, hypothesis-conditioning idioms, and evidence-conditioning idioms. Each category represents a specific modeling objective. Furthermore, we support the use of an idiom-based approach and emphasize the relevance of our collection by combining several of the presented idioms to create a more comprehensive template model. This model can be used in cases involving transfer evidence and disputes over the actor and/or activity. Additionally, we cite literature that employs idioms in template models or case-specific models, providing the reader with examples of their use in forensic casework.
本文介绍了一系列有助于使用贝叶斯网络对法医学中的活动水平评估进行建模的习语。这些习语分为五类：因果习语、叙事习语、综合习语、假设条件习语和证据条件习语。每个类别代表一个特定的建模目标。此外，我们支持使用基于习语的方法，并通过组合几个已呈现的习语来创建一个更全面的模板模型，强调我们所收集习语的相关性。该模型可用于涉及转移证据以及关于行为者和/或活动的争议的案件。此外，我们引用了在模板模型或特定案例模型中使用习语的文献，为读者提供它们在法医案件工作中的使用示例。
