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Record W2137584280 · doi:10.1126/science.1220656

Rapid Variability of Seawater Chemistry Over the Past 130 Million Years

2012· article· en· W2137584280 on OpenAlexaff
Ulrich G. Wortmann, Adina Paytan

Bibliographic record

VenueScience · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSeawaterSulfateEvaporiteCarbonatePrecipitationδ34SEnvironmental chemistrySulfurCarbon cycleChemistryDissolutionOceanographySedimentary rockEnvironmental scienceEarth scienceGeologyMineralogyGeochemistryPaleontologyFluid inclusionsEcologyEcosystemMeteorology

Abstract

fetched live from OpenAlex

Fluid inclusion data suggest that the composition of major elements in seawater changes slowly over geological time scales. This view contrasts with high-resolution isotope data that imply more rapid fluctuations of seawater chemistry. We used a non-steady-state box model of the global sulfur cycle to show that the global δ(34)S record can be explained by variable marine sulfate concentrations triggered by basin-scale evaporite precipitation and dissolution. The record is characterized by long phases of stasis, punctuated by short intervals of rapid change. Sulfate concentrations affect several important biological processes, including carbonate mineralogy, microbially mediated organic matter remineralization, sedimentary phosphorous regeneration, nitrogen fixation, and sulfate aerosol formation. These changes are likely to affect ocean productivity, the global carbon cycle, and climate.

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)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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

Citations132
Published2012
Admission routes1
Has abstractyes

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