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Record W2898988480 · doi:10.1073/pnas.1804250115

Current CaCO <sub>3</sub> dissolution at the seafloor caused by anthropogenic CO <sub>2</sub>

2018· article· en· W2898988480 on OpenAlexafffund
Olivier Sulpis, Bernard P. Boudreau, Alfonso Mucci, David S. Trossman, Brian K. Arbic, Robert M. Key

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsDalhousie UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaNational Science Foundation
KeywordsBenthic zoneDissolutionCalciteSeafloor spreadingOceanographyCarbonateDeep seaGeologyCarbonate compensation depthOcean acidificationOcean chemistryBottom waterEnvironmental scienceCarbonate mineralsEnvironmental chemistryGeochemistrySeawaterChemistry

Abstract

fetched live from OpenAlex

content of deep-sea sediments are combined with a rate model to derive the global distribution of benthic calcite dissolution rates and obtain primary confirmation of an anthropogenic component. By comparing preindustrial with present-day rates, we determine that significant anthropogenic dissolution now occurs in the western North Atlantic, amounting to 40-100% of the total seafloor dissolution at its most intense locations. At these locations, the calcite compensation depth has risen ∼300 m. Increased benthic dissolution was also revealed at various hot spots in the southern extent of the Atlantic, Indian, and Pacific Oceans. Our findings place constraints on future predictions of ocean acidification, are consequential to the fate of benthic calcifiers, and indicate that a by-product of human activities is currently altering the geological record of the deep 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.283
Teacher spread0.257 · 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 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

Citations152
Published2018
Admission routes2
Has abstractyes

Explore more

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