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Record W4205776466 · doi:10.1029/2021gl095020

Effects of Deep Circulation on CaCO<sub>3</sub> Dissolution and Accumulation in the Southwestern Atlantic Ocean

2022· article· en· W4205776466 on OpenAlexaff
Xiaoqing Liu, Yiming Luo, Bernard P. Boudreau

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsDalhousie University
FundersNational Natural Science Foundation of China
KeywordsThermohaline circulationOceanographyGeologyNorth Atlantic Deep WaterSeafloor spreadingBottom waterBenthic zoneDeep seaCarbonateOcean currentCircumpolar deep waterWater massOcean chemistryOceanic basinShutdown of thermohaline circulationAntarctic Bottom WaterStructural basinSeawaterPaleontologyChemistry

Abstract

fetched live from OpenAlex

Abstract Deep oceanic circulation regulates seafloor calcium carbonate (CaCO 3 ) accumulation by transporting atmospheric carbon dioxide (CO 2 ) to depth and then transferring it, with respired CO 2 , along the global ocean conveyor belt. This creates the shallowing trend of CaCO 3 preservation from the Atlantic to the Pacific Oceans. The thermohaline flow can be, however, complex on a basin‐wide scale; here, we use a state‐of‐the‐art data compilation and a carbonate accumulation/dissolution model to explain the CaCO 3 distribution within the basins of the Southwestern Atlantic Ocean. Our results demonstrate that different currents foster systematically dissimilar CaCO 3 preservation within these connected ocean basins. The more undersaturated, faster moving, northward‐flowing Antarctic bottom water readily dissolves more CaCO 3 than the southward‐flowing North Atlantic deep water. We are able to predict quantitatively these observations, based on benthic carbonate chemistry and mass‐transfer rates. Our model and CaCO 3 records in such basins have the potential to provide new understanding about deep‐ocean circulation of the past.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.026
GPT teacher head0.278
Teacher spread0.252 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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