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Record W1987891146 · doi:10.1080/07055900.2001.9649663

Ocean heat transport and a climate paradox

2001· article· en· W1987891146 on OpenAlexafffundvenue
William A. Gough, Margarita Lozinova

Bibliographic record

VenueATMOSPHERE-OCEAN · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of TorontoThe Scarborough Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClimatologyEquatorTemperature gradientOcean currentEnvironmental scienceStratification (seeds)Atmospheric sciencesLatitudePolarZonal and meridionalOceanographyGeologyMeteorologyGeographyPhysicsGeodesy

Abstract

fetched live from OpenAlex

Paleoclimcite data indicate a climate paradox. In warmer climates the equator to pole temperature gradient is typically less than that of the current climate. However, more northward heat transport is required to maintain this weaker gradient, particularly in tropical, subtropical and midlatitude regions where the ice‐albedo feedback and polar stratification of the atmosphere have little effect. Most heat transport mechanisms decrease with decreased temperature gradient. Two oceanic mechanisms that might contribute to a resolution of this paradox are examined, one relies upon salinity re‐distribution, while the other relies upon the non‐linearity of the equation of state. These are tested in a simply configured ocean general circulation model of the North Atlantic. Both are shown to increase northward heat transport without increasing the meridional temperature gradient. The nonlinearity mechanism is the more significant of the two, but neither of the mechanisms can conclusively resolve the paradox.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0000.002
Research integrity0.0010.001
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 head0.221
Teacher spread0.210 · 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

Citations1
Published2001
Admission routes3
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicClimate variability and modelsFrench-language works237,207