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Record W2066106046 · doi:10.3189/2012jog11j165

Carbonaceous particles reveal that Late Holocene dust causes the dark region in the western ablation zone of the Greenland ice sheet

2012· article· en· W2066106046 on OpenAlexaff
I. G. M. Wientjes, Roderik S. W. van de Wal, Margit Schwikowski, Alexander Zapf, Simon Fahrni, Lukas Wacker

Bibliographic record

VenueJournal of Glaciology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsGeologyAblation zoneIce sheetGreenland ice sheetIce coreAeolian processesIce streamHoloceneSea iceTundraCryosphereGeomorphologyOceanographyArcticGlacier

Abstract

fetched live from OpenAlex

Abstract A dark region in the western ablation zone of the Greenland ice sheet is caused by outcropping ice layers that contain more dust than the surrounding brighter ice. These higher amounts of dust were deposited in the accumulation zone of the ice sheet and travelled with the ice to the ablation zone. To deduce the period and the causes of this higher dust deposition, carbonaceous particles in ice samples from the dark region and from brighter reference ice were analysed and used for dating. Samples including ice from directly below the surface contain high amounts of modern organic carbon, probably from microorganisms on the ice surface. Deeper samples reveal low amounts of carbonaceous particles, which are originally deposited in the accumulation zone. The amount of outcropping carbonaceous particles in the dark region seems significantly higher than in the reference ice. One of the samples that contained material initially deposited in the accumulation zone was dated and revealed Late Holocene ages, coinciding with a period of enhanced eolian activity in the nearby tundra. Therefore, variable eolian activity during the Holocene effected dust fluxes towards the ice and hence leads to albedo variations in the present ablation zone of the ice sheet.

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 score0.010
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.044
GPT teacher head0.264
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

Citations43
Published2012
Admission routes1
Has abstractyes

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