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Record W3112795873 · doi:10.17816/snv201982221

Middle-Don Neolithic culture: problems of selection, chronology and periodization

2019· article· en· W3112795873 on OpenAlexaboutno aff
Aleksey Surkov

Bibliographic record

VenueSamara Journal of Science · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPeriodizationQuarter (Canadian coin)ChronologyPopulationExcavationAncient historyHistoryArchaeologyDemographySociology

Abstract

fetched live from OpenAlex

The paper deals with the main results of the Middle-Don Neolithic culture study. The contribution of A.T. Sinyuk is noted. The paper also contains some evolution of his views on the content of the early stage of the culture. So, the first periodization, done in 1971 as a result of Universitetskaya III site study, was then adjusted, especially after the excavations of Monastyrskaya I site. The culture chronology according to modern concepts fits into the IV-V millennium BC. The origin of the Middle-Don culture is debatable. New absolute dating allows us to consider the early stage in the first half of the VI - third quarter of the VI millennium BC and associate it with the first monuments with stroke ceramics and plate stone inventory. The author notes that there was an interaction of the Middle Don population with the Karamyshevsky population at the early stage. During the last quarter of the VI - first quarter of V millennium BC stroke-ornamented-comb ware spread, ornament completely filled the outer surface of the vessels. Late stage - second quarter V - end V millennium BC, the syncretic types were formed. Vestigial stage - the beginning of IV millennium BC, there was an end of Middle-Don traditions, they were rare in the Rybnoozersky type of ceramics.

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)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0020.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.228
Teacher spread0.204 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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