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Climate Factor in Cultural Transformations of Eurasia in the Mid-4Th – Mid-3Rd Millennia BC, and Possibilities of Creating an Absolute Chronology

2024· article· en· W4401337879 on OpenAlexaboutno aff
Stanislav Grigoriev

Bibliographic record

VenueComechingonia Revista de Arqueología · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsChronologyMegalithRadiocarbon datingGeographyPeriod (music)Climate changeAncient historyQuarter (Canadian coin)Black seaPlateau (mathematics)ArchaeologyHistoryGeologyOceanographyArt

Abstract

fetched live from OpenAlex

Climate changes were the most important factor that stimulated migration in antiquity. It was they which led to the appearance of monuments of the megalithic tradition in the Northwestern Black Sea region (Usatovo), in the North Caucasus (Novosvobodnaya), in the Urals, and in Central Asia (Chemurchek) in the 4th – 3rd millennia B.C. This also caused the spread of the tradition of Yamnaya culture to Central Europe, the appearance of the Corded Ware cultures and many other changes. However, the general process of climate change could not be a trigger for migrations. These were short-term drastic climatic changes, which are recorded by dendrochronology. The latter can also be used as chronological markers, making it possible to create the Eurasian chronology independent of radiocarbon analyses, which have too wide confidence intervals. This approach made it possible to determine the date of the Yamnaya migration to the Carpathian Basin and the formation of the Corded Ware cultures ca. 2850 B.C., and the date of the Fatyanovo migration from Europe to the east ca. 2564 B.C. Unfortunately, the dates of the appearance of megaliths in the east are not determined with a similar accuracy, due to the impossibility to verify this with alternative sources. Their appearance can be dated to ca. the mid-4th millennium B.C. in Eastern Europe, in the last quarter of the 4th millennium B.C. in the Urals, and in the 24th century B.C. in Central Asia.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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

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 head0.253
Teacher spread0.237 · 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.

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
Published2024
Admission routes1
Has abstractyes

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