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Record W2598342431 · doi:10.1002/2017gl073138

North Pacific twentieth century decadal‐scale variability is unique for the past 342 years

2017· article· en· W2598342431 on OpenAlexaff
B. Williams, Jochen Halfar, Kristine L. DeLong, E. Smith, Robert S. Steneck, P. A. Lebednik, Dorrit E. Jacob, Jan Fietzke, G. W. K. Moore

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArchipelagoPacific decadal oscillationClimatologyStormOceanographyPacific oceanGeologySea surface temperature

Abstract

fetched live from OpenAlex

Abstract Reconstructed sea surface temperatures (SSTs) derived from Mg/Ca measurements in nine encrusting coralline algal skeletons from the Aleutian archipelago in the northernmost Pacific Ocean reveal an overall increase in SST from 1665 to 2007. In the Aleutian SST reconstruction, decadal‐scale variability is a transient feature present during the 1700s and early 1800s and then fully emerging post‐1950. SSTs vary coherently with available instrument records of cyclone variance and vacillate in and out of coherence with multicentennial Pacific Northwest drought reconstructions as a response to SST‐driven alterations of storm tracks reaching North America. These results indicate that an influence of decadal‐scale variability on the North Pacific storm tracks only became apparent during the midtwentieth century. Furthermore, what has been assumed as natural variability in the North Pacific, based on twentieth century instrumental data, is not consistent with the long‐term natural variability evident in reconstructed SSTs predating the anthropogenic influence.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.041
GPT teacher head0.315
Teacher spread0.274 · 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

Citations19
Published2017
Admission routes1
Has abstractyes

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