RESUMO
OBJECTIVES: Recovery rates reflect the amount of recovered skeletal materials based on expectations about the total number of elements or individuals that should be present in an assemblage. It is an underlying concept that reflects analytical potential, wherein high recovery rates typically indicate high analytical capabilities. However, numerous methods are available to calculate different types of recovery rates, and each method addresses various types of research questions and utilizes different variables. Therefore, recovery rates cannot be applied and compared directly, and the appropriate recovery rate for any given research question must be considered thoughtfully. MATERIALS AND METHODS: Several methods of determining individual and element recovery rates are applied to the USS Oklahoma commingled human remains assemblage and discussed with regard to their utility. RESULTS: Depending on which method is used, recovery rates range from 91 to 102% for the recovery of individuals and 0.02 to 91% for the recovery of elements within this assemblage. DISCUSSION: These results emphasize the need to carefully consider which recovery rate is most appropriate based on associated research questions and project contexts. We introduce the idea of the analytical recovery rate, a flexible concept to determine the potential assessment of biological profile parameters once individuation of commingled remains has occurred, wherein elements are selected based on the needs of the project as well as element preservation.
Assuntos
Restos Mortais/anatomia & histologia , Osso e Ossos/anatomia & histologia , Antropologia Forense/métodos , Adulto , Havaí , História do Século XX , Humanos , Militares/históriaRESUMO
During the analysis of a commingled human remains assemblage, pair-matching is often conducted as part of the inventory to inform the DNA sampling strategy and to calculate the minimum or most likely number of individuals. As commingled assemblages become larger, pair-matching becomes more difficult, and it is unknown whether accuracy declines. Therefore, a study to determine the accuracy rates of visual pair-matching for multiple observers was conducted on a large, commingled human assemblage. The sample consisted of 580 left and right humeri (n = 287 and n = 293, respectively) from the commingled remains of the USS Oklahoma, which were undergoing analysis at the Defense POW/MIA Accounting Agency. Five anthropologists completed this study, determining humeri pairs with varying degrees of confidence and non-pairs. The overall precision was 81.0% and ranged from 74.1% to 95.9% for participants, including all confidence levels. When considering only confident matches, the overall precision for all participants increased to 91.4%.
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This study reviews recent advances in osteometric, genetic, geochemical, and digital modeling applications since 2014 to demonstrate the expanded range of analyses and skeletal elements that can be used to separate individuals from commingled contexts. While traditional methods remain foundational to commingling resolution, new advances allow increased individuation, identification of human versus non-human remains, and an amplified scale of assemblages that can be analyzed. This summary offers ways for practitioners to consider the juxtaposition of analytical goals, time, financial concerns, and methods when managing commingled assemblages. Forensic anthropology and bioarchaeology case studies illustrate differences related to application of methods in terms of recovery environments, project goals, and recovered materials. Whether the goal is to isolate and individuate only major elements or as many bones as possible, in nearly all cases, it is best practice to combine several types of methods to fulfill the project scope within the established parameters. This review can help practitioners identify the most appropriate analytical protocols and methods for their projects.
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Evaluation of method performance involves the consideration of numerous factors that can contribute to error. A variety of measures of performance can be borrowed from the signal detection literature and others are drawn from statistical science. This article demonstrates the principles of performance evaluation by applying multiple measures to osteometric sorting models for paired elements run against data from known individuals. Results indicate that false positive rates are close, on average, to expected values. As assemblage size grows, the false positive rate becomes unimportant and the false negative rate becomes significant. Size disparity among the commingled individuals plays a significant role in method performance, showing that case-specific circumstances (e.g. assemblage size and size disparity) will determine method power.
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Although there are numerous reliable multivariate models for sex estimation, many scenarios, both forensic and archaeological, result in the recovery of fragmentary remains, which prevents the collection of various standard measurements. The purpose of this research was to establish metric applications for sex estimation from the distal humerus and distal radius of European/American Whites and American Blacks. Data for this research were retrieved from a sample consisting of a larger database from multiple skeletal collections. Measurements include epicondylar breadth, breadth of the capitulum-trochlea, and distal breadth of the radius. Student's t-test and descriptive statistics were utilized to analyze the data. Classification rates ranged from 75% to 96.4%, with the capitulum-trochlea breadth performing best. Overall, significant metric differences exist between the sexes in the distal humerus and radius and can be utilized to estimate sex. This study offers a reliable alternative sex estimation technique applicable to fragmentary or damaged remains.
Assuntos
Úmero/anatomia & histologia , Rádio (Anatomia)/anatomia & histologia , Determinação do Sexo pelo Esqueleto/métodos , Feminino , Antropologia Forense , Humanos , Masculino , Grupos RaciaisRESUMO
This study compares the original pair-matching osteometric sorting model (J Forensic Sci 2003;48:717) against two new models providing validation and performance testing across three samples. The samples include the Forensic Data Bank, USS Oklahoma, and the osteometric sorting reference used within the Defense POW/MIA Accounting Agency. A computer science solution to generating dynamic statistical models across a commingled assemblage is presented. The issue of normality is investigated showing the relative robustness against non-normality and a data transformation to control for normality. A case study is provided showing the relative exclusion power of all three models from an active commingled case within the Defense POW/MIA Accounting Agency. In total, 14,357,220 osteometric t-tests were conducted. The results indicate that osteometric sorting performs as expected despite reference samples deviating from normality. The two new models outperform the original, and one of those is recommended to supersede the original for future osteometric sorting work.