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Record W1845717730 · doi:10.1080/00438243.2015.1078740

Evaluating the impact of Black Sea flooding on the Neolithic of northern Turkey

2015· article· en· W1845717730 on OpenAlexafffund
Peter Bikoulis

Bibliographic record

VenueWorld Archaeology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsHoloceneShoreFlood mythPrehistoryPeriod (music)Black seaFlooding (psychology)GeographyArchaeologyHistoryGeologyOceanography

Abstract

fetched live from OpenAlex

Originally formulated based on marine geological research concerned with the timing and tempo of the Black Sea infilling, the Black Sea flood Hypothesis (BSfH) argues that this process was a catastrophic event ~7150 BP that greatly impacted the prehistoric peoples who lived along the ancient shoreline. The resulting mass migration of peoples led to great transformations across Europe and southwest Asia. Continued research in the region has challenged the timing and impact of the event, arguing instead that it was neither sudden nor catastrophic. However, the BSfH continues to be invoked as a plausible explanation for the lack of early Holocene or Neolithic period sites in northern Turkey. Results from spatial modelling along the Turkish coast suggest that the explanatory power of the BSfH to explain this absence is exaggerated. Rather, other environmental and social factors must be considered in explaining the complete lack of early Holocene sites across the region.

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)0.001
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 score0.106
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.303
Teacher spread0.221 · 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

Citations8
Published2015
Admission routes2
Has abstractyes

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