Sentence examples for forensic comparisons from inspiring English sources

Standard forensic comparisons employing mtDNA are typically straightforward.

In forensics, mtDNA typing is most commonly employed when the nuclear DNA in an evidentiary sample is too limited or too damaged to develop sufficient nuclear data for forensic comparisons.

A forensic comparison of the YouTube evidence can't quite prove this sensational claim either way but you really, really want it to be true.

In 1996, the authors of an exhaustive study of forensic hair comparisons published in the Columbia Human Rights Law Review concluded, "If the purveyors of this dubious science cannot do a better job of validating hair analysis than they have done so far, forensic hair comparison analysis should be excluded altogether from criminal trials".

Only few data are available on the individual mutation rate around position 573 and more research is needed to evaluate this and other length variant regions to determine how these should be treated in forensic database comparisons.

And although LHP is not routinely used in forensic match comparisons of Sanger-based CR haplotypes [14,15], accurate sequence alignment in LHP regions will likely still be desirable as the field transitions to MPS for routine mtDNA data generation.

Heteroplasmic variation of either type is not used for exclusionary purposes in forensic match comparisons of mtDNA profiles, owing to both (1) the high mutation rate of mtDNA and the germ-line bottleneck in oogenesis, which can result in complete homoplasmic shifts between generations [16,17] and (2) the variation that has been observed between different tissue types [18 24].

A mismatched condition was further created by using a combination of high-quality studio-clean and degraded mobile-landline recordings in the forensic voice comparison system.

Automatic forensic voice comparison (FVC) systems employed in forensic casework have often relied on Gaussian Mixture Model - Universal Background Models (GMM-UBMs) for modelling with relatively little research into supervector-based approaches.

This paper examines the impact on the speech signal of a key feature of these networks, namely dynamic rate coding, and its subsequent impact on the task of likelihood-ratio-based forensic voice comparison (FVC).

Forensic voice comparison (FVC) systems have often employed Gaussian Mixture Model - Universal Background Models (GMM-UBMs) [1-3] for modelling in forensic casework, in which it is common that only a very small speech database is available for the entire system development.