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Record W4285410040 · doi:10.24852/pa2022.1.39.159.177

Stone Hammers of Ananyino Cultural and Historical Area

2022· article· en· W4285410040 on OpenAlexaboutno aff
Andrei A. Chizhevsky

Bibliographic record

VenuePovolzhskaya Arkheologiya (The Volga River Region Archaeology) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHammerQuarter (Canadian coin)Period (music)ChronologyRange (aeronautics)HistoryPosition (finance)GeographyArchaeologyEngineeringArtMechanical engineering

Abstract

fetched live from OpenAlex

The paper addresses the origin, chronology and use of stone hammers of the Ananyino Cultural and Historical Area. Stone hammers were commonly used in the pre-Scythian period across the steppe zone of Eastern Europe and in the North Caucasus. Two categories of these items were spread in the territory of the Ananyino Cultural and Historical Area - equal-arm hammers and axe-hammers. The paper features evidence of local manufacture of axe-hammers, whereas such evidence is presently not available for equal-arm hammers. Placing hammers in burials next to weapons and depicting them on steles in the same position as military metal axes and socketed axes make it possible to be attribute them to weapons. The existence period of stone hammers has been determined within a wide range of the 9th – first half of the 7th enturies BC, and within a narrow range of the mid-8th – first quarter/first half of the 7th century BC.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.087
GPT teacher head0.245
Teacher spread0.158 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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