Suppr超能文献

足部骨骼的性别和人群归属

Attribution of foot bones to sex and population groups.

作者信息

Smith S L

机构信息

Department of Sociology and Anthropology, University of Texas at Arlington, USA.

出版信息

J Forensic Sci. 1997 Mar;42(2):186-95.

PMID:9068176
Abstract

Although cranial and pelvic bones are the preferred skeletal material used by forensic anthropologists to assign unknown individuals to their most probable sex and population (racial) groups, these remains may be unavailable. This paper presents models for classification using metatarsals, proximal pedal phalanges, and the first distal phalanx of the foot. Measurements include lengths and mediolateral and dorsoplantar widths of these foot bones. Four samples of 40 individuals each (black and white males and females) comprise the dataset. Models were developed separately for right and left sides. Three models are provided for each side: a metatarsal model, a proximal phalangeal model, and a combination model involving selected metatarsal and phalangeal measurements. A stepwise discriminant procedure was used for variable selection, with some highly correlated (r > 0.85) variables subsequently removed. The metatarsal models correctly assign approximately 77-84% of individuals to their correct sex and population groups; proximal phalangeal models yield correct assignments in 70-72% of cases, and the combination models give correct classifications in 87% of cases. Models exchanging variables selected from one side for corresponding variables on the other show discriminating power ranging from approximately 67-86%. More conservative "jackknife" estimates give correct assignments in 64-82% of cases. When these models are used for classification of sex alone, 86.2-93.7% ("jackknife" range, 84.3-91.2%) of cases are correctly classified; for race alone, 78.6-96.2% ("jackknife" range, 75.5-92.4%).

摘要

尽管颅骨和骨盆骨是法医人类学家用于将不明身份个体归为最可能的性别和人群(种族)群体的首选骨骼材料,但这些遗骸可能无法获取。本文提出了使用跖骨、近节趾骨和足部第一远节趾骨进行分类的模型。测量包括这些足部骨骼的长度以及内外侧和背跖侧宽度。四个样本,每个样本有40名个体(黑人与白人男性和女性)构成了数据集。分别针对右侧和左侧开发了模型。每侧提供了三个模型:一个跖骨模型、一个近节趾骨模型以及一个涉及选定跖骨和趾骨测量值的组合模型。采用逐步判别程序进行变量选择,随后去除了一些高度相关(r > 0.85)的变量。跖骨模型能将大约77 - 84%的个体正确归为其正确的性别和人群群体;近节趾骨模型在70 - 72%的案例中能得出正确归类,组合模型在87%的案例中能给出正确分类。用一侧选择的变量替换另一侧相应变量的模型显示出的判别能力在大约67 - 86%之间。更保守的“留一法”估计在64 - 82%的案例中能给出正确归类。当这些模型仅用于性别分类时,86.2 - 93.7%(“留一法”范围为84.3 - 91.2%)的案例能被正确分类;仅用于种族分类时,78.6 - 96.2%(“留一法”范围为75.5 - 92.4%)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验