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Record W3084557134 · doi:10.1002/jqs.3241

A continuous tephrostratigraphic record from the Labrador Sea spanning the last 65 ka

2020· article· en· W3084557134 on OpenAlexaboutno aff
Sunniva Rutledal, Haflidi Haflidason, Lisa Griem, Eystein Jansen

Bibliographic record

VenueJournal of Quaternary Science · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsTephraGeologyTephrochronologyVolcanoMarine isotope stageIce coreSedimentOceanographyStage (stratigraphy)Deposition (geology)Glacial periodPaleontologyPhysical geographyInterglacialGeography

Abstract

fetched live from OpenAlex

ABSTRACT Volcanic ash preserved in marine sediment sequences is key for independent synchronization of palaeoclimate records within and across different climate archives. Here we present a continuous tephrostratigraphic record from the Labrador Sea, spanning the last 65–5 ka, an area and time period that has not been investigated in detail within the established North Atlantic tephra framework. We investigated marine sediment core GS16‐204‐22CC for increased tephra occurrences and geochemically analysed the major element composition of tephra shards to identify their source volcano(es). In total we observed eight tephra zones, of which five concentration peaks show isochronous features that can be used as independent tie‐points in future studies. The main transport mechanism of tephra shards to the site was near‐instantaneous deposition by drifting of sea ice along the East Greenland Current. Our results show that the Icelandic Veidivötn volcanic system was the dominant source of tephra material, especially between late Marine Isotope Stage (MIS) 4 and early MIS 3. The Veidivötn system generated volcanic eruptions in cycles of ca. 3–5 ka. We speculate that the quantity of tephra delivered to the Labrador Sea was a result of variable Icelandic ice volume and/or changes in the transportation pathway towards the Labrador Sea.

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)0.002
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 score0.023
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.254
Teacher spread0.220 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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