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Record W2460652787 · doi:10.1594/pangaea.833626

Age determination and faunal composition of sediments off northern Greenland

2014· dataset· en· W2460652787 on OpenAlexaboutno aff
Niels Nørgaard‐Pedersen, Naja Mikkelsen, Susanne Lassen, Yngve Kristoffersen, Emma Sheldon

Bibliographic record

VenueFigshare · 2014
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsComposition (language)GeologyOceanographyPaleontologyPhysical geographyGeographyArt

Abstract

fetched live from OpenAlex

We present a record encompassing marine isotope stages 7-1 from a hitherto unexplored and heavily ice-covered area of the Arctic Ocean, the Lomonosov Ridge off the northern Greenland-Canada continental margin, using nannofossil and benthic foraminifera stratigraphy. Planktic foraminifera assemblages are used as a key paleoceanographic proxy, and a surprisingly large variability is found for an interior Arctic Ocean site. Abundant small (63-125 µm) subpolar Turborotalita quinqueloba occur in two sections, possibly representing substages 5e (last interglacial) and 5a (warm interstadial). However, the present-day circulation pattern and the very distant location of high productive regions cannot explain such high abundances of subpolar specimens in the interior, perennially sea ice-covered Arctic Ocean. Hence our proxy record indicates that last interglacial sea ice concentrations were reduced off some areas of northern Greenland-Canada. Whether this was part of a larger regional pattern or it represents the influence of polynya areas with locally increased productivity remains to be solved. With respect to glacial conditions, increased ice-rafted debris (IRD) deposition in the area appears to be associated with glacial stages 6, 4, and late 3. Stage 2 sediments (including the Last Glacial Maximum) are condensed with a sparse IRD content only.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.271
Threshold uncertainty score0.540

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.224
Teacher spread0.192 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2014
Admission routes1
Has abstractyes

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