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Kieran P. McNulty

Researcher at University of Minnesota

Publications -  71
Citations -  1279

Kieran P. McNulty is an academic researcher from University of Minnesota. The author has contributed to research in topics: Vegetation (pathology) & Crania. The author has an hindex of 18, co-authored 65 publications receiving 1142 citations. Previous affiliations of Kieran P. McNulty include Baylor University & Durham University.

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Neanderthal taxonomy reconsidered: Implications of 3D primate models of intra- and interspecific differences

TL;DR: The hypothesis that Neanderthals represent a subspecies of H. sapiens is tested by comparing the degree of their morphological differentiation from modern humans to that found within and between 12 species of extant primates.
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Size, shape, and asymmetry in fossil hominins: The status of the LB1 cranium based on 3D morphometric analyses

TL;DR: Results from the whole cranium demonstrated that aspects of facial morphology associated with smaller size converge on modern human morphology, suggesting that facial similarities between LB1 and anatomically modern humans may not be indicative of a close relationship.
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The Pleistocene archaeology and environments of the Wasiriya Beds, Rusinga Island, Kenya.

TL;DR: The Wasiriya Beds of Rusinga Island, Kenya, preserve a Pleistocene sedimentary archive with radiocarbon age estimates of >33-45 ka that contains Middle Stone Age artifacts and abundant, well-preserved fossil fauna: a co-occurrence rare in eastern Africa, particularly in the region bounding Lake Victoria.
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Examining affinities of the Taung child by developmental simulation.

TL;DR: Developmental simulation estimates the adult form of the Taung child and directly compares its morphology to that of other fossil hominins, indicating that morphology already present by occlusion of the first permanent molar is the primary determinant of adult form and supporting use of extant trajectories to estimate the morphology of an extinct species.
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The shape of human evolution: a geometric morphometrics perspective.

TL;DR: While multivariate methods offered clear advantages over univariate or bivariate representations of shape, the analysis of traditional morphometric measures such as linear distances, angles, and ratios, has limitations when it comes to quantifying the complex geometry of some anatomical structures.