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Record W1965720988 · doi:10.5194/bg-12-3043-2015

Pleistocene sediment offloading and the global sulfur cycle

2015· article· en· W1965720988 on OpenAlexafffund
Stefan Marković, Adina Paytan, Ulrich G. Wortmann

Bibliographic record

VenueBiogeosciences · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSulfur cycleSedimentationSedimentδ34SPyriteGeologyErosionSulfurContinental shelfQuaternaryOceanographySea levelSulfateHoloceneEnvironmental scienceGeochemistryPaleontologyChemistryHydrothermal circulation

Abstract

fetched live from OpenAlex

Abstract. Quaternary sea level fluctuations have greatly affected the sediment budgets of the continental shelves. Previous studies suggested that this caused a considerable increase in the net loss of shelf sediments. Since sediment accumulation and erosion are closely tied to the formation and re-oxidation of pyrite, we use a high-resolution record of sulfur isotope ratios (34S / 32S) of marine sulfate to evaluate the implications of the so-called "shelf sediment offloading" on the global sulfur cycle. Modeling of our δ34S record suggests that erosion during sea level lowstands was only partly compensated by increased sedimentation during times of rising sea level and sea level highstands. Furthermore, our data suggests that shelf systems reached a new equilibrium state about 700 ka, which considerably slowed or terminated shelf sediment offloading.

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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.258
Teacher spread0.229 · 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

Citations35
Published2015
Admission routes2
Has abstractyes

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