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Record W2793108263 · doi:10.1038/s41598-018-22453-z

Black Sea outflow response to Holocene meltwater events

2018· article· en· W2793108263 on OpenAlexafffund
Jens O. Herrle, Jörg Bollmann, Christina Gebühr, Hartmut Schulz, Rosie M. Sheward, Annika Giesenberg

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaSenckenberg Biodiversität und Klima ForschungszentrumUniversity of TorontoEberhard Karls Universität TübingenDeutscher Akademischer Austauschdienst
KeywordsMeltwaterHoloceneOceanographyGeologyIce sheetGreenland ice sheetNorth Atlantic oscillationSea levelGlacial periodPhysical geographyGeographyPaleontology

Abstract

fetched live from OpenAlex

During the Holocene, North American ice sheet collapse and rapid sea-level rise reconnected the Black Sea with the global ocean. Rapid meltwater releases into the North Atlantic and associated climate change arguably slowed the pace of Neolithisation across southeastern Europe, originally hypothesized as a catastrophic flooding that fueled culturally-widespread deluge myths. However, we currently lack an independent record linking the timing of meltwater events, sea-level rise and environmental change with the timing of Neolithisation in southeastern Europe. Here, we present a sea surface salinity record from the Northern Aegean Sea indicative of two meltwater events at ~8.4 and ~7.6 kiloyears that can be directly linked to rapid declines in the establishment of Neolithic sites in southeast Europe. The meltwater events point to an increased outflow of low salinity water from the Black Sea driven by rapid sea level rise >1.4 m following freshwater outbursts from Lake Agassiz and the final decay of the Laurentide ice sheet. Our results shed new light on the link between catastrophic sea-level rise and the Neolithisation of southeastern Europe, and present a historical example of how coastal populations could have been impacted by future rapid sea-level rise.

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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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

Citations25
Published2018
Admission routes2
Has abstractyes

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