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Record W2005164294 · doi:10.1002/ajpa.20479

Osteoarthritis in Siberia's Cis‐Baikal: Skeletal indicators of hunter‐gatherer adaptation and cultural change

2006· article· en· W2005164294 on OpenAlexaff
Angela R. Lieverse, Andrzej Weber, Vladimir Ivanovich Bazaliiskiy, Olga I. Goriunova, Nikolai A. Savel’ev

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of AlbertaMemorial University of Newfoundland
Fundersnot available
KeywordsHiatusSubsistence agricultureHoloceneAdaptive strategiesHunter-gathererGeographyForagingAdaptation (eye)EcologyDemographyEthnologyArchaeologyBiologyHistorySociologyPaleontology

Abstract

fetched live from OpenAlex

This examination of osteoarthritis in Siberia's Cis-Baikal region focuses on the reconstruction of mid-Holocene mobility and activity patterns with particular interest in an alleged fifth millennium BC biocultural hiatus. Five cemetery populations--two representing the pre-hiatus Kitoi culture (6800-4900 BC) and three the post-hiatus Serovo-Glaskovo (4200-1000 BC)-are considered. The objective is to investigate osteoarthritic prevalence and distribution (patterning) within and among these populations in order to reconstruct mobility and activity patterns among the Cis-Baikal foragers, and to test for possible disparities that may reflect differing adaptive strategies. The data reveal that levels of activity remained relatively constant throughout the mid-Holocene but that mobility and specific activity patterns did not. Although results are consistent with the current understanding of distinct Kitoi and Serovo-Glaskovo subsistence regimes, specifically the lower residential mobility and narrower resource base of the former, they also draw attention to adaptive characteristics shared by all occupants of the Cis-Baikal.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.265
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations102
Published2006
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Physical AnthropologySame topicForensic Anthropology and Bioarchaeology StudiesFrench-language works237,207