Evidence map›Paper›PMID 27826647›Full record

ArticleInternational journal of legal medicine2017

Sex estimation from the long bones of modern South Africans.

Gabriele C Krüger, Ericka N L'Abbé, Kyra E Stull

Abstract read
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Article in International journal of legal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
37.5field-weighted citation impact, top 1% 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

25 citing papers in PubMed, 76 citations in OpenAlex.

  1. Article
  2. Article
  3. Constancy of Sexual Dimorphism in the Infracranial Skeleton.American journal of biological anthropology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Sex assessment from contemporary Mexican postcranial long bones.International journal of legal medicine · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Sex estimation from long bones: a machine learning approach.International journal of legal medicine · 2023
    Article
  18. Article
  19. Article
  20. 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

3 authors at 2 institutions in 2 countries.

Gabriele C KrügerDepartment of Anatomy, Faculty of Health Sciences, University of Pretoria, Private Bag X323, Arcadia, 0007, South Africa. gabi.kruger@up.ac.za.
Ericka N L'AbbéDepartment of Anatomy, Faculty of Health Sciences, University of Pretoria, Private Bag X323, Arcadia, 0007, South Africa.
Kyra E StullDepartment of Anthropology, University of Nevada, 1664 North Virginia Street, Reno, NV, 89557-0096, USA.
University of Pretoria · ZAUniversity of Nevada, Reno · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Best scientific practice for sex estimation incorporates accurate techniques that employ appropriate standards and population- and period-specific data. Single measurements provide accurate sex estimations, but multiple measurements and multivariate techniques offer greater validity to biological profile assessments. Appropriate, modern standards for sex estimation are limited to the cranium in South Africans (SA), which warrants the examination of the potential for sex estimation using the postcrania of socially defined SA blacks, whites and coloureds through multivariate models and advanced statistical techniques. A total of 39 standard osteometric measurements were taken from the postcrania of 360 socially defined SA blacks, whites and coloureds (equal sex and ancestry). Univariate and multivariate models were evaluated. Multivariate models, with cross-validation and equal priors, were explored with linear and flexible discriminant analysis (LDA and FDA, respectively). Classification accuracies associated with univariate models ranged from 56 to 89%, whereas multivariate classification accuracies using bone models (i.e. all measurements from one element) ranged from 75 to 91%. The highest correct classifications were achieved with multivariate subsets (i.e. combinations of measurements from different bones) and ranged from 90 to 98%. Overall, FDA and LDA yielded similar accuracy rates. Postcranial bones achieve comparable classification accuracies to the pelvis and higher accuracies than metric or morphological techniques using the cranium. While LDA is the most commonly used classification statistic in biological anthropology, FDA provides a good alternative for classification.

Indexed as

AdolescentAdultAgedAged, 80 and overBlack PeopleBone and BonesDiscriminant AnalysisFemaleHumansMaleMiddle AgedSex Determination by SkeletonSouth AfricaWhite PeopleYoung AdultAdvanced statistical analysesFlexible discriminant analysisPostcranialSex classificationSexual dimorphism

Identifiers

PMID27826647
OpenAlexW2555323079

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.