MétaCan
Menu
← Back to cohort
Record W4313477367 · doi:10.1038/s41598-022-27315-3

Formation of the North Atlantic Warming Hole by reducing anthropogenic sulphate aerosols

2023· article· en· W4313477367 on OpenAlexaboutno aff
Yuki Kusakabe, Toshihiko Takemura

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceMinistry of EnvironmentEnvironmental Restoration and Conservation Agency
KeywordsEnvironmental scienceOceanographyGlobal warmingClimate changeGeology

Abstract

fetched live from OpenAlex

Abstract The North Atlantic Warming Hole (NAWH) has been observed and predicted due to the increase in carbon dioxide (CO 2 ) concentration. If sulphate aerosols, which have a cooling effect on the atmosphere, are reduced by air pollution control, the NAWH may form as it would if CO 2 concentrations increased. In this study, sensitivity experiments using a coupled atmosphere–ocean-aerosol model were conducted by varying the amount of sulphur dioxide (SO 2 ) emissions, a precursor of sulphate which is the primary anthropogenic aerosol in the atmosphere, to analyse the changes in the ocean temperature, salinity, and density. The results showed that although the spatial patterns of the NAWH due to the changes in SO 2 emissions was similar to that due to the changes in the CO 2 concentrations, the magnitude of the shifts in the ocean parameters due to the changes in SO 2 emissions is larger even when changes in global mean temperature are comparable. This can be due to the spatial concentration of sulphate aerosols in the mid-latitudes of the Northern Hemisphere, resulting larger changes in the heat transport from the south on the Gulf Stream and the North Atlantic Current along with changes in freshwater inflow from the Arctic through the Labrador Sea.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations10
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueScientific Reports→Same topicAtmospheric and Environmental Gas Dynamics→French-language works237,207→