Evidence map›Paper›PMID 30788449›Full record

ArticleForensic sciences research2018

Exploring non-invasive approaches to assist in the detection of clandestine human burials: developing a way forward.

Soren Blau, Jon Sterenberg, Patrick Weeden, Fernando Urzedo, Richard Wright, Chris Watson

Abstract read
In one paragraph

Article in Forensic sciences research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Soren BlauVictorian Institute of Forensic Medicine, Melbourne, Australia.ORCID https://orcid.org/0000-0001-6499-7741
Jon SterenbergVictorian Institute of Forensic Medicine, Melbourne, Australia.
Patrick WeedenScout Aerial, Brisbane, Queensland, Australia.ORCID 0000-0002-0877-5375
Fernando UrzedoScout Aerial, Brisbane, Queensland, Australia.ORCID 0000-0001-6172-035X
Richard WrightUniversity of Sydney, Sydney, Australia.
Chris WatsonNew South Wales (NSW) Office of Environment and Heritage, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The analyses of physical evidence recovered from clandestine single and mass graves have been demonstrated to be of significant evidential and/or investigative value for both court purposes and humanitarian investigations. The detection of these types of graves is, therefore, pivotal to forensic investigations. This article reviews different remote and ground-based methods that have been used to attempt to detect deliberately concealed burial sites and summarizes the experimental research that has, to date, been undertaken in order to improve grave detection. The article then presents the preliminary findings of research being undertaken at the Australian Facility for Taphonomic Experimental Research (AFTER). This research, the first of its kind to be undertaken in the southern hemisphere, is based on experimental single and mass graves using human cadavers. The research is centred on current remote sensing methods and techniques combined with the analysis of the effects of below-ground temperature and moisture and ground-based weather data. It is hoped that identifying successful sensors and detectors will be beneficial to national and international agencies that are involved in forensic as well as humanitarian investigations that require the detection of deliberately concealed gravesites.

Indexed as

burialclandestine gravesdetectionforensic anthropologyForensic sciencemass gravesremote sensing

Identifiers

PMID30788449
PMCPMC6374940

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.