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Record W2411065602 · doi:10.1002/2016pa002945

The minor sulfur isotope composition of Cretaceous and Cenozoic seawater sulfate

2016· article· en· W2411065602 on OpenAlexaff
Andrew L. Masterson, Boswell A. Wing, Adina Paytan, James Farquhar, David T. Johnston

Bibliographic record

VenuePaleoceanography · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsMcGill University
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsGeologySeawaterSulfatePyriteEvaporiteBiogeochemical cycleCretaceousGeochemistryIsotopeSulfurWeatheringPopulationMineralogyOceanographyEnvironmental chemistryPaleontologySedimentary rockChemistry

Abstract

fetched live from OpenAlex

Abstract The last 125 Myr capture major changes in the chemical composition of the ocean and associated geochemical and biogeochemical cycling. The sulfur isotopic composition of seawater sulfate, as proxied in marine barite, is one of the more perplexing geochemical records through this interval. Numerous analytical and geochemical modeling approaches have targeted this record. In this study we extend the empirical isotope record of seawater sulfate to therefore include the two minor sulfur isotopes, 33S and 36S. These data record a distribution of values around means of Δ33S and Δ36S of 0.043 ± 0.016‰ and −0.39 ± 0.15‰, which regardless of δ34S‐based binning strategy is consistent with a signal population of values throughout this interval. We demonstrate with simple box modeling that substantial changes in pyrite burial and evaporite sulfate weathering can be accommodated within the range of our observed isotopic values.

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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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