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  1. Brain structure is predicted by social network size but not other key social attributes in free-ranging monkeys. 
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  2. Abstract

    In carnivorans, bite force is a critical and ecologically informative variable that has been correlated with multiple morphological, behavioral, and environmental attributes. Whereas in vivo measures of biting performance are difficult to obtain in many taxa—and impossible in extinct species—numerous osteological proxies exist for estimating masticatory muscle size and force. These proxies include both volumetric approximations of muscle dimensions and direct measurements of muscular attachment sites. In this study, we compare three cranial osteological techniques for estimating muscle size (including 2D‐photographic and 3D‐surface data approaches) against dissection‐derived muscle weights and physiological cross‐sectional area (PCSA) within the jaw adductor musculature of 40 carnivoran taxa spanning eight families, four orders of magnitude in body size, and the full dietary spectrum of the order. Our results indicate that 3D‐approaches provide more accurate estimates of muscle size than do surfaces measured from 2D‐lateral photographs. However, estimates of a muscle's maximum cross‐sectional area are more closely correlated with muscle mass and PCSA than any estimates derived from muscle attachment areas. These findings highlight the importance of accounting for muscle thickness in osteological estimations of the masticatory musculature; as muscles become volumetrically larger, their larger cross‐sectional area does not appear to be associated with a proportional increase in the attachment site area. Though volumetric approaches approximate muscle dimensions well across the order as a whole, caution should be exercised when applying any single method as a predictor across diverse phylogenies.

     
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  3. Abstract Objectives

    Predicting body mass is a frequent objective of several anthropological subdisciplines, but there are few published methods for predicting body mass in immature humans. Because most reference samples are composed of adults, predicting body mass outside the range of adults requires extrapolation, which may reduce the accuracy of predictions. Prediction equations developed from a sample of immature humans would reduce extrapolation for application to small‐bodied target individuals, and should have utility in multiple predictive contexts.

    Materials and Methods

    Here, we present two novel body mass prediction equations derived from 3468 observations of stature and bi‐iliac breadth from a large sample of immature humans (n = 173) collected in the Harpenden Growth Study. Prediction equations were generated using raw and natural log‐transformed data and modeled using panel regression, which accounts for serial autocorrelation of longitudinal observations. Predictive accuracy was gauged with a global sample of human juveniles (n = 530 age‐ and sex‐specific annual means) and compared to the performance of the adult morphometric prediction equation previously identified as most accurate for human juveniles.

    Results

    While the raw data panel equation is only slightly more accurate than the adult equation, the logged data panel equation generates very accurate body mass predictions across both sexes and all age classes of the test sample (mean absolute percentage prediction error = 2.47).

    Discussion

    The logged data panel equation should prove useful in archaeological, forensic, and paleontological contexts when predictor variables can be measured with confidence and are outside the range of modern adult humans.

     
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