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Record W2062237254 · doi:10.1175/jcli4273.1

Rapid Holocene Deglaciation of the Labrador Sector of the Laurentide Ice Sheet

2007· article· en· W2062237254 on OpenAlexaboutno aff
Anders E. Carlson, Peter U. Clark, G. M. Raisbeck, Edward J. Brook

Bibliographic record

VenueJournal of Climate · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsDeglaciationHoloceneGeologyIce sheetOceanographyLast Glacial MaximumGlacial periodGreenland ice sheetPhysical geographyQuaternaryChronologySea levelPleistoceneClimatologyPaleontologyGeography

Abstract

fetched live from OpenAlex

Abstract Retreat of the Laurentide Ice Sheet (LIS) following the Last Glacial Maximum 21 000 yr BP affected regional to global climate and accounted for the largest proportion of sea level rise. Although the late Pleistocene LIS retreat chronology is relatively well constrained, its Holocene chronology remains poorly dated, limiting our understanding of its role in Holocene climate change and sea level rise. Here new 10Be cosmogenic exposure ages on glacially deposited boulders are used to date the final disappearance of the Labrador sector of the LIS (LS-LIS). These data suggest that following the deglaciation of the southeastern Hudson Bay coastline at 8.0 ± 0.2 cal ka BP, the southwestern margin of the LS-LIS rapidly retreated ∼600 km in 140 yr and most likely in ∼600 yr at a rate of ∼900 m yr−1, with final deglaciation by 6.8 ± 0.2 10Be ka. The disappearance of the LS-LIS ∼6.8 10Be ka and attendant reduction in freshwater runoff may have induced the formation of Labrador Deep Seawater, while the loss of the high albedo surface may have initiated the Holocene Thermal Maximum in eastern Canada and southern Greenland. Moreover, the rapid melting just prior to ∼6.8 10Be ka indicates that the remnant LIS may be the primary source of a postulated rapid rise in global sea level of ∼5 m that occurred sometime between 7.6 and 6.5 cal ka BP.

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 score0.005
Threshold uncertainty score0.873

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 studies0.0000.000
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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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

Citations69
Published2007
Admission routes1
Has abstractyes

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