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Record W4308231084 · doi:10.29173/anlk637

Early Holocene Human Burials from Fa Hien-lena and Kuragala, Sri Lanka

2022· article· en· W4308231084 on OpenAlexaff
Jay T. Stock, Emma Pomeroy, Oshan Wedage, Saman Eregama, Siran Deraniyagala, Nimal Perera, Patrick Roberts, Nicole Boivin, Michael D. Petraglia

Bibliographic record

VenueAncient Lanka · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of CalgaryWestern University
Fundersnot available
KeywordsHoloceneTaphonomyPrehistoryArchaeologyPleistoceneContext (archaeology)Rock shelterGeographyPaleoanthropologyHuman boneBioarchaeologyBiology

Abstract

fetched live from OpenAlex

Few human burials from Sri Lankan archaeological contexts have been described. Here we report on the analysis of two early Holocene skeletons, FH8, a young adult female skeleton excavated from Fa Hien-lena and dated to 10,640-10,139 cal BP, and BK1, a middle adult male skeleton excavated at Kuragala and dated to 7,170-6,950 cal BP. The skeletons are both highly fragmentary, which poses challenges for their thorough analysis. However, this paper describes the archaeological context, mortuary treatment and archaeothanatology of the burials, post-mortem taphonomy of human remains, the osteobiography of both individuals, and some general observations on their morphology relative to one another and a broader range of late Pleistocene and Holocene foragers. The results demonstrate common elements of funerary treatment between these two burials, such as interment on the left side with right hands placed near or over the face. The FH8 individual died at a young age and shows some signs of early childhood stress. Both skeletons show moderate to high degrees of tooth wear for their relative ages, and no evidence for dental disease. The body size estimates of FH8 and BK1 fall in the range that would be expected of tropical or temperate forest foragers, although BK1 has a relatively low body mass relative to stature, which aligns his phenotype with populations of more arid environments. We demonstrate that much can be potentially learned about human populations and prehistoric behaviours from skeletal analyses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.240
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

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