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Record W2000835964 · doi:10.1002/ajpa.21313

Activity‐induced dental modification in holocene siberian hunter‐fisher‐gatherers

2010· article· en· W2000835964 on OpenAlexaff
Andrea L. Waters‐Rist, Vladimir I. Bazaliiskii, Andrzej Weber, Olga I. Goriunova, M. Anne Katzenberg

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsGroove (engineering)HoloceneArchaeologyGeographySubsistence agricultureRegional variationBiologyDentistryMedicine

Abstract

fetched live from OpenAlex

The use of teeth as tools provides clues to past subsistence patterns and cultural practices. Five Holocene period hunter-fisher-gatherer mortuary sites from the south-western region of Lake Baikal, Siberia, Russian Federation, are observed for activity-induced dental modification (AIDM) to further characterize their adaptive regimes. Grooves on the occlusal surfaces of teeth are observed in 25 out of 123 individuals (20.3%) and were most likely produced during the processing of fibers from plants and animals, for making items such as nets and cordage. Regional variation in the frequency of individuals with occlusal grooves is found in riverine versus lakeshore sites. This variation suggests that production of material culture items differed, perhaps in relation to different fishing practices. There is also variation in the distribution of grooves by sex: grooves are found predominately in females, except at the Late Neolithic-Bronze Age river site of Ust'-Ida I where grooves are found exclusively in males. Occlusal grooves were cast using polyvinylsiloxane and maxillary canine impressions were examined by scanning electron microscopy (SEM) to determine striation patterns. Variation in striae orientation suggests that a variety of activities, and/or different manufacturing techniques, were involved in groove production. Overall, the variability in occlusal groove frequency, sex and regional distribution, and microscopic striae patterns, points to the multiplicity of activities and ways in which people used their mouths and teeth in cultural activities.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.037
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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; a candidate call from one teacher head, not a consensus.

Study designQualitative
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

Citations37
Published2010
Admission routes1
Has abstractyes

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