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Record W2125158094 · doi:10.1002/2015gl065779

Gas hydrate dissociation prolongs acidification of the Anthropocene oceans

2015· article· en· W2125158094 on OpenAlexafffund
Bernard P. Boudreau, Yiming Luo, Filip J. R. Meysman, Jack J. Middelburg, Gerald R. Dickens

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClathrate hydrateCarbonateAnthropoceneOcean acidificationCarbon cycleCarbon dioxideBiogeochemical cycleMethaneEnvironmental scienceOceanographyEnvironmental chemistryGeologyEarth scienceHydrateEcosystemClimate changeChemistryEcologyPaleontology

Abstract

fetched live from OpenAlex

Abstract Anthropogenic warming of the oceans can release methane (CH4) currently stored in sediments as gas hydrates. This CH4 will be oxidized to CO2, thus increasing the acidification of the oceans. We employ a biogeochemical model of the multimillennial carbon cycle to determine the evolution of the oceanic dissolved carbonate system over the next 13 kyr in response to CO2 from gas hydrates, combined with a reasonable scenario for long‐term anthropogenic CO2 emissions. Hydrate‐derived CO2 will appreciably delay the neutralization of ocean acidity and the return to preindustrial‐like conditions. This finding is the same with CH4 release and oxidation in either the deep ocean or the atmosphere. A change in CaCO3 export, coupled to CH4 release, would intensify the transient rise of the carbonate compensation depth, without producing any changes to the long‐term evolution of the carbonate system. Overall, gas hydrate destabilization implies a moderate additional perturbation to the carbonate system of the Anthropocene oceans.

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 score0.006
Threshold uncertainty score0.012

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 science0.0000.001
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 head0.040
GPT teacher head0.304
Teacher spread0.264 · 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

Citations46
Published2015
Admission routes2
Has abstractyes

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