2018
DOI: 10.1016/j.forsciint.2018.04.048
|View full text |Cite
|
Sign up to set email alerts
|

Experimental sharp force injuries to ribs: Multimodal morphological and geometric morphometric analyses using micro-CT, macro photography and SEM

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
8
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 24 publications
(10 citation statements)
references
References 26 publications
2
8
0
Order By: Relevance
“…It is important to note that a variety of cut mark dimensions and morphological characteristics are expected when using different knife blade types; the difference in the blades’ cutting edge characteristics is reported earlier in Figure 1 ; cut marks created and examined in this study have characteristics which are in general agreement with previous studies [ 8 , 51 53 ]. The profile of the cut marks inflicted by a non-serrated blade was found to be linear-shaped, a narrow cross-section, and with no striations which are indications of this knife type.…”
Section: Discussionsupporting
confidence: 89%
See 2 more Smart Citations
“…It is important to note that a variety of cut mark dimensions and morphological characteristics are expected when using different knife blade types; the difference in the blades’ cutting edge characteristics is reported earlier in Figure 1 ; cut marks created and examined in this study have characteristics which are in general agreement with previous studies [ 8 , 51 53 ]. The profile of the cut marks inflicted by a non-serrated blade was found to be linear-shaped, a narrow cross-section, and with no striations which are indications of this knife type.…”
Section: Discussionsupporting
confidence: 89%
“…In this study, an increased percentage with kerf striations in the cut marks inflicted by fine-serrated (67%) and coarse-serrated (60%) blades and the lack of this characteristic in the cut marks inflicted by a non-serrated blade indicate that kerf striations are useful to distinguish knife class, as found by others [ 20 , 50 ]. In addition, the morphology of the striations varied with the two different types of serrated knives, indicating that the blade/teeth size and thickness influence the striations, as also found in other studies [ 14 , 53 ]. A fine-serrated blade usually produces smaller and more delicate kerf striations because it interacts closely with a bone surface.…”
Section: Discussionsupporting
confidence: 81%
See 1 more Smart Citation
“…2 In A, histogram showing the distribution of the included papers which have been published in the selected time interval (i.e., from 2001 to 2021) and demonstrating the increasing interest in the topic in the last five years; in B types of biological or non-biological materials investigated by micro-CT in the 93 included papers (i.e., in two of the included studies more than one biological or non-biological material was investigated; therefore, a total 99 classifiable items was considered. See Supplemental material for detailed classification data) light microscopy [33,34]. Together, the results of several experimental studies demonstrated the value of this technique for measuring saw mark features (i.e., top and bottom kerf width, depth, angles degrees, and floor width) validating its use for this type of injuries.…”
Section: Tool Markmentioning
confidence: 67%
“…In BSM taphonomy, GMM were initially introduced as a means of quantifying cut mark morphologies for both 2D derived data [ 50 ] and entire 3D models [ 51 ]. These advances have obtained exceptional resolutions, presenting means of identifying the lithic tool and raw material used to produce each cut mark in archaeology [ 50 52 , inter alia ], while also arising in forensic research for sharp force trauma identification [ 53 , 54 , inter alia ]. Likewise, initial efforts in the quantification of tooth score and pit morphologies reached up to 80% classification rates differentiating between carnivore agencies [ 55 58 ], with Machine Learning algorithms obtaining > 95% accuracy [ 58 , 59 ].…”
Section: Introductionmentioning
confidence: 99%