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Record W2104809317 · doi:10.1177/0959683611400465

Connecting the Atlantic-sector and the north Pacific (Mt Logan) ice core stable isotope records during the Holocene: The role of El Niño

2011· article· en· W2104809317 on OpenAlexaffabout
David Fisher

Bibliographic record

VenueThe Holocene · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of OttawaGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsIce coreHoloceneGeologyOceanographyArcticClimatologySeries (stratigraphy)Physical geographyGeographyPaleontology

Abstract

fetched live from OpenAlex

The δ( 18 O) Holocene of the Mt Logan ice core is very different from those of eastern Arctic Canada and Greenland. The large changes seen in Logan dwarf even the largest change (the cooling event 8200 years ago) in the Atlantic-sector cores. Large changes in Logan’s δ( 18 O) and d are related to the state of El Niño as reflected by the Quelccaya δ( 18 O) series. It is found that the lagged auto-difference series of the ice core records from the Agassiz ice cap, Greenland and the 23-site stack of paleotemperature records of Kaufman et al. (Kaufman DS, Schneider DP, McKay NP, Ammann CM, Bradley RS, Briffa KR et al. (2009) Recent warming reverses long-term Arctic cooling. Science 325: 1236) produce highly significant matches to the Mt Logan δ( 18 O) series. These correspondences suggest a lag of 1200 years. This lag time is what some models of the Diffusive-Great Ocean Conveyor (D-GOC) predict for the average travel time from the North Atlantic to the tropical eastern Pacific. Monte Carlo testing of the correlations show that they are very significant. The implications of ENSO being affected by the difference between temperatures today and those of 1200 years ago are touched on.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.999

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 studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.219
Teacher spread0.192 · 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.

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

Citations14
Published2011
Admission routes2
Has abstractyes

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