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Record W2913301470 · doi:10.1038/s41467-019-08307-w

Rapidly receding Arctic Canada glaciers revealing landscapes continuously ice-covered for more than 40,000 years

2019· article· en· W2913301470 on OpenAlexaboutno aff
Simon L. Pendleton, Gifford H. Miller, Nathaniel A. Lifton, Scott J. Lehman, John Southon, Sarah E. Crump, Robert S. Anderson

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersUniversity of Colorado BoulderNational Science Foundation
KeywordsGlacierArcticPhysical geographyThe arcticGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract Arctic temperatures are increasing faster than the Northern Hemisphere average due to strong positive feedbacks unique to polar regions. However, the degree to which recent Arctic warming is unprecedented remains debated. Ages of entombed plants in growth position preserved by now receding ice caps in Arctic Canada help to address this issue by placing recent conditions in a multi-millennial context. Here we show that pre-Holocene radiocarbon dates on plants collected at the margins of 30 ice caps in Arctic Canada suggest those locations were continuously ice covered for > 40 kyr, but are now ice-free. We use in situ 14C inventories in rocks from nine locations to explore the possibility of brief exposure during the warm early Holocene. Modeling the evolution of in situ 14C confirms that Holocene exposure is unlikely at all but one of the sites. Viewed in the context of temperature records from Greenland ice cores, our results suggest that summer warmth of the past century exceeds now any century in ~115,000 years.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.213

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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 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

Citations62
Published2019
Admission routes1
Has abstractyes

Explore more

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