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Record W2345846719 · doi:10.1594/pangaea.836222

Foraminifera in sediment cores of the Lomonosov Ridge and Morris Jesup Rise

2013· dataset· en· W2345846719 on OpenAlexaboutno aff
Daniela Hanslik, Ludvig Löwemark, Martin Jakobsson

Bibliographic record

VenueFigshare · 2013
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsRidgeForaminiferaGeologyPaleontologyGeochemistryOceanography

Abstract

fetched live from OpenAlex

X-ray fluorescence (XRF) scanning of sediment cores from the Lomonosov Ridge and the Morris Jesup Rise reveals a distinct pattern of Ca intensity peaks through Marine Isotope Stages (MIS) 1 to 7. Downcore of MIS 7, the Ca signal is more irregular and near the detection limit. Virtually all major peaks in Ca coincide with a high abundance of calcareous microfossils; this is particularly conspicuous in the cores from the central Arctic Ocean. However, the recorded Ca signal is generally caused by a combination of biogenic and detrital carbonate, and in areas influenced by input from the Canadian Arctic, detrital carbonates may effectively mask the foraminiferal carbonates. Despite this, there is a strong correlation between XRF-detected Ca content and foraminiferal abundance. We propose that in the Arctic Ocean north of Greenland a common palaeoceanographic mechanism is controlling Ca-rich ice-rafted debris (IRD) and foraminiferal abundance. Previous studies have shown that glacial periods are characterized by foraminfer-barren sediments. This implies that the Ca-rich IRD intervals with abundant foraminifera were most likely deposited during interglacial periods when glaciers left in the Canadian Arctic Archipelago were still active and delivered a large amount of icebergs. At the same time, conditions were favourable for planktic foraminifera, resulting in a strong covariance between these proxies. Therefore, we suggest that the XRF scanner's capability to efficiently map Ca concentrations in sediment cores makes it possible to systematically examine large numbers of cores from different regions to investigate the palaeoceanographic reasons for the calcareous microfossils' spatial and temporal variability.

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 score0.306
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.043
GPT teacher head0.216
Teacher spread0.173 · 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
Published2013
Admission routes1
Has abstractyes

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