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Record W2020076207 · doi:10.1002/ajpa.20286

Interpersonal violence at Lepenski Vir Mesolithic/Neolithic complex of the Iron Gates Gorge (Serbia‐Romania)

2005· article· en· W2020076207 on OpenAlexafffund
Mirjana Roksandić, Marija Djurić, Zoran Rakočević, Kimberly Seguin

Bibliographic record

VenueAmerican Journal of Physical Anthropology · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMesolithicContext (archaeology)Interpersonal violenceGeographyForagingArchaeologyDemographyEcologyPoison controlSociologySuicide preventionBiologyMedicine

Abstract

fetched live from OpenAlex

The Mesolithic populations of the Danube River's Iron Gates Gorge (Serbia/Romania) spanned over 1,500 years (from before 7000 bc to around 5500 bc) in one of the most favorable foraging environments of Europe. Over most of these 1,500 years, the dominant economy was foraging, but farming was practiced by communities in the region from around 6500 bc. This research examines individuals from four sites on the Danube (Lepenski Vir, Vlasac, Padina, and Hajducka Vodenica) whose traumatic lesions can be most plausibly interpreted as resulting from violent interactions. Given over four hundred individuals buried at these sites (MNI = 418), the episodes of violent interactions were few and without evidence of a specific temporal pattern. They probably represent sporadic episodes of interpersonal conflict that do not support the notion of endemic warfare deemed typical of the Mesolithic, or elevated levels of interpersonal/intertribal conflict at the time of contact with farming communities. The difference in patterns of violence between the Mesolithic sites on the right bank of the Danube and a coeval site of Schela Cladovei on the left bank is explained in terms of differences in archaeological context, geographic location, and possibly specific local histories.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.999

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 studies0.0010.111
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.269
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations49
Published2005
Admission routes2
Has abstractyes

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