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Comment on egusphere-2024-819

2024· peer-review· en· W4395668136 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Abstract. Dansgaard-Oeschger (DO) events are a pervasive feature of glacial climates. It is widely accepted that the associated changes in climate, which are most pronounced in the North Atlantic region, are caused by abrupt changes in the strength and/or latitude reach of the Atlantic meridional overturning circulation (AMOC), possibly originating from spontaneous transitions in the ocean-sea-ice-atmosphere system. Here we use an Earth System Model that produces DO-like events to show that the climate conditions under which millennial-scale AMOC variations occur are controlled by the surface ocean buoyancy flux. In particular, we find that the present day-like convection pattern with deep water formation in the Labrador and Nordic Seas becomes unstable when the buoyancy flux integrated over the northern North Atlantic turns from negative to positive. It is in the proximity of this point that the model produces transitions between different convection patterns associated with strong and weak AMOC states. The buoyancy flux depends on the surface freshwater and heat fluxes and on sea surface temperature through the temperature dependence of the thermal expansion coefficient of seawater. We find that larger ice sheets tend to stabilize convection by decreasing the net freshwater flux while CO2-induced cooling decreases buoyancy loss and destabilizes convection. These results help to explain the conditions under which DO events appear, and are a step towards an improved understanding of the mechanisms of abrupt climate changes.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.444
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0130.007
Insufficient payload (model declined to judge)0.4440.307

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 head0.051
GPT teacher head0.271
Teacher spread0.220 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2024
Admission routes1
Has abstractyes

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