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Record W2168439910 · doi:10.1029/2001pa000639

Arctic ice export events and their potential impact on global climate during the late Pleistocene

2002· article· en· W2168439910 on OpenAlexfundno aff
Dennis A. Darby, Jens Bischof, Robert F. Spielhagen, Steven A. Marshall, S. Herman

Bibliographic record

VenuePaleoceanography · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersEidgenössische Technische Hochschule ZürichUniversity of AlbertaBarnard CollegeOregon State UniversityNational Science FoundationYale UniversityNorsk PolarinstituttAarhus Universitet
KeywordsGeologyIce sheetOceanographyArcticArctic ice packIcebergPleistoceneGreenland ice sheetAntarctic sea iceIce shelfSea iceIce coreIce streamCryospherePaleontologyPhysical geographyGeography

Abstract

fetched live from OpenAlex

Ice sheets in the North American Arctic and, to a lesser extent, those in northern Eurasia calved large quantities of icebergs that drifted through Fram Strait into the Greenland Sea several times during the late Pleistocene. These icebergs deposited Fe oxide grains (45–250 μm) and coarse lithic clasts >250 μm matched to specific circum‐Arctic sources. Four massive Arctic iceberg export events are identified from the Laurentide and the Innuitian ice sheets, between 14 and 34 ka (calendar years) in a sediment core from Fram Strait. These relatively short duration (<1–4 kyr) events contain 3–5 times the background levels of Fe oxide grains. They began suddenly, as indicated by a steep rise in the number of grains matched to an ice sheet source, suggesting rapid purges of ice through Fram Strait, due perhaps to collapse of ice sheets. The larger events from the northwestern Laurentide ice sheet are preceded by events from the Innuitian ice sheet. Despite the chronological uncertainties, the Arctic export events appear to occur prior to Heinrich events.

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)0.001
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.012
GPT teacher head0.224
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 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

Citations115
Published2002
Admission routes1
Has abstractyes

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