Helen Litavec* | Binghamton University Abstract: Commingled human remains can result in a significant loss of information regarding the individuals present and make the biological profile difficult to establish. One common technique for separating commingled remains at joint surfaces is osteometric sorting.1 However, current models have only been applied to large joints of the body, for instance the hip or knee, while smaller joints like the sacroiliac (SI) or first tarsometatarsal (1st TMT) joint are unable to be sorted. Osteometric sorting separates commingled joints with a singular width measurement.1 However, linear measurements may be limited in their ability to describe the entirety of joint surfaces.2 Therefore, this study’s first hypothesis is that commingled individuals can be sorted at the SI and 1st TMT joints using osteometric sorting. The second hypothesis is that the joint surface area values will exclude more potential matches than the width measurements. The measurements and surface area values were calculated from virtual models created from the William M. Bass Donated Skeletal Collection. The left os coxae, sacra, medial cuneiforms, and first metatarsals of 56 individuals were scanned with a SHINING 3D® EinScan Pro 2X Plus handheld surface scanner. Each articular surface was cropped from the virtual model, and the widest portion of each facet was measured with the distance tool while the surface area was calculated using the compute area function in Geomagic Wrap 2017. The measurements were recorded in a Microsoft Excel Workbook, where the osteometric sorting models were also calculated.1 Four reference samples were formed to generate the models: SI width (Model 1), SI surface area (Model 2), 1st TMT width (Model 3), and 1st TMT surface area (Model 4). Each sample was composed of 51 known individuals with varying demographics. Shapiro-Wilks tests were conducted to identify any outliers. These four models were then used to identify commingled individuals in the four test samples. Each test sample consisted of five known individuals and 20 artificially commingled pairs. Each model’s efficiency was calculated as an indicator of overall success at determining the correct classification rate of true positives and negatives.3 In all test samples, several potential pairs were excluded through the implementation of the new models. Model 1 was the least efficient (0.28) and only eliminated 10% of the commingled pairs. Model 2 was the most efficient (0.72) and correctly rejected 65% of the commingled pairs. Furthermore, two of the true SI joints were correctly reassociated using Model 2. Model 3 excluded 60% of the commingled pairs; however, it also eliminated one of the true matches (efficiency = 0.64). A similar result occurred for Model 4, where only 45% of commingled pairs were rejected as well as one true match (efficiency = 0.52). These results illustrate that osteometric sorting can help exclude potential matches at these particular joints. If future researchers are interested in osteometric sorting at these joints, then the reference sample sizes should be increased. References 1. Byrd, John E., and Carrie B. LeGarde. “Chapter 8 - Osteometric Sorting.” In Commingled Human Remains, edited by Bradley J. Adams and John E. Byrd, 167–191. Academic Press (2014). https://doi.org/10.1016/B978-0-12-405889-7.00008-3. 2. Rösing, F. W., and E. Pischtschan. "Re-individualisation of commingled skeletal remains." Advances in Forensic Sciences 7 (1995): 38–41. 3. Byrd, John E., and Carrie B. LeGarde. "Evaluation of method performance for osteometric sorting of commingled human remains." Forensic Sciences Research 3, no. 4 (2018): 343–349. https://doi.org/10.1080/20961790.2018.1535762.