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Record W3206459074 · doi:10.24852/pa2021.3.37.142.154

Reconstruction of the Settlement Levoberezhnoe Plan of the Bronze Age (South Ural, Russia)

2021· article· en· W3206459074 on OpenAlexaboutno aff
В.В. Носкевич, Н. В. Федорова, Fedor N. Petrov

Bibliographic record

VenuePovolzhskaya Arkheologiya (The Volga River Region Archaeology) · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)ArchaeologyExcavationBronze AgeBronzeGeographyQuarter (Canadian coin)GeologyAncient historyHistory

Abstract

fetched live from OpenAlex

In the Southern Urals in 2015–2019 research was conducted on the fortified settlement of the Bronze Age Levoberezhnoe (Sintashta II). An asphalt road was drawn through the settlement, during the construction of which about a third of the monument’s area was destroyed. Excavations of the monument have been carried out since 2015. It has been established that the settlement is multi-layered; it functioned in the Late Bronze Age from the turn of the 3rd–2nd millennium BC until the last quarter of the second millennium BC. Detailed magnetic and topographic surveys were performed on the territory that remaining survived the construction of the road. The location of the external moat was reliably determined by linear positive magnetic anomalies. The base of the outer wall of the settlement had a thickness of about 4 m, the width of the outer moat was 2–2.5 m. It was also possible to accurately localize a number of walls of buildings. The settlement had a rectangular shape, inside there were 26 dwellings. As a result of a comprehensive analysis of the data and aerial photographs of the last century, the layout of the entire settlement was reconstructed.

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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.190
Teacher spread0.168 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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