Evidence map›Paper›PMID 34106426›Full record

ArticleForensic science, medicine, and pathology2021

Computerized delineation of the teeth and comparison with a smiling photograph: identification of a body skeletonized by cadaverous ichthyofauna action.

Murilo Sérgio Valente-Aguiar, Talita Lima Castro-Espicalsky, Teresa Magalhães, Ricardo Jorge Dinis-Oliveira

Abstract readCase Reports
PubMed Publisher
In one paragraph

Article in Forensic science, medicine, and pathology, 2021. 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
8.8field-weighted citation impact, top 3% of its field
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, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

4 authors at 1 institution in 2 countries.

Murilo Sérgio Valente-AguiarDepartment of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, Porto, Portugal. up201707626@med.up.pt.ORCID 0000-0003-4623-7022
Talita Lima Castro-EspicalskyLegal Medical Institute of Porto Velho, Civil Police of the State of Rondônia, Porto Velho, Brazil.
Teresa MagalhãesDepartment of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, Porto, Portugal.
Ricardo Jorge Dinis-OliveiraDepartment of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, Porto, Portugal. ricardinis@med.up.pt.ORCID 0000-0001-7430-6297
Universidade do Porto · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amazonian's forensic experts usually experience considerable difficulties in the identification of drowned bodies rescued from the rivers of the Amazon basin, since they are frequently found skeletonized by the action of the cadaverous ichthyofauna. In these circumstances, especially when the soft tissues are completely absent, bones and teeth may represent the unique source of information for the identification of the body. This work reports a case of positive identification of a body skeletonized by scavenger ichthyofauna. The identification was performed by comparing computerized delineation of the dental characteristics of the cadaver with those observed in a smiling photograph of the victim. This report also highlights the ferocity of Cetopsis candiru (candiru cobra), Cetopsis coecutiens (candiru-açu) and Calophysus macropterus (piracatinga).

Indexed as

DrowningSmilingCadaverForensic DentistryHumansRiversCadaverous ichthyofaunaDental photographyForensic DentistrySmile

Identifiers

PMID34106426
OpenAlexW3166554050

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.