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Record W2098745683 · doi:10.14430/arctic695

Accumulation in East Greenland Fjords and on the Continental Shelves Adjacent to the Denmark Strait over the Last Century Based on 210Pb Geochronology

2002· article· en· W2098745683 on OpenAlexvenueno aff
L. Micaela Smith, Clark Alexander, Anne Jennings

Bibliographic record

VenueARCTIC · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsFjordGeologyOceanographySedimentContinental shelfHoloceneGlacial periodMeltwaterGeomorphology

Abstract

fetched live from OpenAlex

Sediment (SAR) and mass (MAR) accumulation rates for the last 100 years are derived from 210Pb profiles of box cores collected in three fjords and on the continental shelf in the Kangerlussuaq region, East Greenland, and on the SW Iceland continental shelf. The MAR is lower on East Greenland (0.09 g/cm²·yr) than on SW Iceland (0.14 g/cm²·yr) because of differences in the biogenic component of the sediments, although SAR is similar. The differences in accumulation rates of the three East Greenland fjords are due to their dominant sediment sources and basin areas. Kangerlussuaq Fjord, the largest fjord, is dominated by iceberg sediment input and has a MAR of 0.43 g/cm²·yr at 50 km from the fjord head. Miki Fjord, the smallest fjord, is dominated by glaciofluvial sediment input with a MAR of 0.29 g/cm²·yr of sediment at 10 km from the fjord head. Nansen Fjord is intermediate in size, with an iceberg-dominated sediment supply; MAR is 1.01 g/cm²·yr near the fjord head and 0.17 g/cm²·yr at 20 km from the fjord head. 137Cs is used as a secondary indicator of sediment source, and the high activity level of 137Cs in Miki Fjord indicates glaciofluvial sediment sources. Zones of constant activity in some of the box cores are attributed to either bioturbation in the surface mixed layer or turbidites. We would be hesitant to extend the recent 210Pb-based accumulation rates to estimate the Holocene accumulation rates.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.245
Teacher spread0.213 · 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.

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
Published2002
Admission routes1
Has abstractyes

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