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Transition analysis 3: Skeletal age estimation program.

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Title: Transition analysis 3: Skeletal age estimation program.
Authors: Boldsen, Jesper L.1 (AUTHOR), Heissel, Thomas Wulff1,2 (AUTHOR), Getz, Sara M.3 (AUTHOR), Weise, Svenja1 (AUTHOR), Boock, Magnus Victor2 (AUTHOR), Cruz-Filipe, Luís4 (AUTHOR), Ousley, Stephen D.1,5 (AUTHOR), Milner, George R.1,6 (AUTHOR) ost@psu.edu
Source: Forensic Science International. Sep2026, Vol. 386, pN.PAG-N.PAG. 1p.
Subjects: Human skeleton, Maximum likelihood statistics, Forensic anthropology, Skeletal maturity, Archaeological dating, Musculoskeletal system physiology
Abstract: Estimating the age of adult human skeletons through a combination of multiple age-of-transition curves is facilitated through the development of a computer program, TA3-V1.0. Curves were generated for 47 skeletal structures and 69 transitions from one stage to the next. Data were derived from 1638 modern known-age skeletons from four continents, a diverse sample designed to accommodate human variation in genetic origin, cultural affiliation, and activity patterns. The TA3-V1.0 program generates point estimates of age (maximum likelihood estimates) and confidence intervals (80, 90, and 95%). Researchers often encounter incomplete remains, so individualized estimates are tailored to the anatomical structures that are present as well as their appearance. Several built-in prior distributions accommodate specific forensic and archaeological needs. The TA3-V1.0 program permits the estimation of age throughout adulthood. With an old-age adjustment, the correlation between true (reported) and estimated ages using skeletons from this sample is 0.92; without the correction, it is 0.91. • Age throughout adulthood is estimated from human skeletal remains. • Maximum likelihood point estimates and age intervals are produced. • Age estimates are tailored to the combination of skeletal structures and stages present. • Built-in prior distributions meet specific investigator needs. • Point estimates and age intervals correspond closely to true ages. [ABSTRACT FROM AUTHOR]
Copyright of Forensic Science International is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="JN" term="%22Forensic+Science+International%22">Forensic Science International</searchLink>. Sep2026, Vol. 386, pN.PAG-N.PAG. 1p.
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  Label: Abstract
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  Data: Estimating the age of adult human skeletons through a combination of multiple age-of-transition curves is facilitated through the development of a computer program, TA3-V1.0. Curves were generated for 47 skeletal structures and 69 transitions from one stage to the next. Data were derived from 1638 modern known-age skeletons from four continents, a diverse sample designed to accommodate human variation in genetic origin, cultural affiliation, and activity patterns. The TA3-V1.0 program generates point estimates of age (maximum likelihood estimates) and confidence intervals (80, 90, and 95%). Researchers often encounter incomplete remains, so individualized estimates are tailored to the anatomical structures that are present as well as their appearance. Several built-in prior distributions accommodate specific forensic and archaeological needs. The TA3-V1.0 program permits the estimation of age throughout adulthood. With an old-age adjustment, the correlation between true (reported) and estimated ages using skeletons from this sample is 0.92; without the correction, it is 0.91. • Age throughout adulthood is estimated from human skeletal remains. • Maximum likelihood point estimates and age intervals are produced. • Age estimates are tailored to the combination of skeletal structures and stages present. • Built-in prior distributions meet specific investigator needs. • Point estimates and age intervals correspond closely to true ages. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Forensic Science International is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.forsciint.2026.112909
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      – Code: eng
        Text: English
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      – SubjectFull: Human skeleton
        Type: general
      – SubjectFull: Maximum likelihood statistics
        Type: general
      – SubjectFull: Forensic anthropology
        Type: general
      – SubjectFull: Skeletal maturity
        Type: general
      – SubjectFull: Archaeological dating
        Type: general
      – SubjectFull: Musculoskeletal system physiology
        Type: general
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      – TitleFull: Transition analysis 3: Skeletal age estimation program.
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            NameFull: Boldsen, Jesper L.
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            NameFull: Heissel, Thomas Wulff
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            – D: 01
              M: 09
              Text: Sep2026
              Type: published
              Y: 2026
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              Value: 386
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