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Record W2750906922 · doi:10.3189/2015jog15j054

Coastal ice-core record of recent northwest Greenland temperature and sea-ice concentration

2015· article· en· W2750906922 on OpenAlexaboutno aff
E. C. Osterberg, R. L. Hawley, G. J. Wong, Ben Kopec, D. G. Ferris, Jennifer A. Howley

Bibliographic record

VenueJournal of Glaciology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersDivision of Arctic SciencesNational Science Foundation
KeywordsSea iceBayGeologyOceanographyArctic ice packIce coreNorth Atlantic oscillationClimatologyIce sheetCryosphereArctic sea ice declineArcticAntarctic sea ice

Abstract

fetched live from OpenAlex

Abstract Coastal ice cores provide an opportunity to investigate regional climate and sea-ice variability in the past to complement hemispheric-scale climate reconstructions from ice-sheet-interior ice cores. Here we describe robust proxies of Baffin Bay temperature and sea-ice concentration from the coastal 2Barrel ice core collected in the Thule region of northwest Greenland. Over the 1990–2010 record, 2Barrel annually averaged methanesulfonic acid (MSA) concentrations are significantly correlated with May–June Baffin Bay sea-ice concentrations and summer temperatures. Higher MSA is observed during warmer years with less sea ice, indicative of enhanced primary productivity in Baffin Bay. Similarly, 2Barrel annually averaged deuterium excess (d-excess) values are significantly correlated with annual Baffin Bay sea-ice concentrations and summer and annual temperatures. Warm (cool) years with anomalously low (high) sea-ice concentration are associated with proportionally more (less) low-d-excess Baffin Bay moisture at the ice-core site. Multilinear regression models incorporating 2Barrel MSA, d-excess and snow accumulation account for 38–51% of the Baffin Bay sea-ice and temperature variance. The annual temperature model is significantly correlated with temperatures throughout most of Greenland and eastern Arctic Canada due to the strong influence of the North Atlantic Oscillation and Atlantic Multidecadal Oscillation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.247

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)0.0000.000

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 head0.024
GPT teacher head0.239
Teacher spread0.215 · 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

Citations23
Published2015
Admission routes1
Has abstractyes

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