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Record W2532484715 · doi:10.1111/sed.12335

Quantifying the volcanic emissions which triggered Oceanic Anoxic Event 1a and their effect on ocean acidification

2016· article· en· W2532484715 on OpenAlexafffund
Kohen W. Bauer, Richard E. Zeebe, Ulrich G. Wortmann

Bibliographic record

VenueSedimentology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyAnoxic watersCarbonateCarbonate compensation depthCarbon cycleOcean acidificationVolcanoIsotopes of carbonSaturation (graph theory)OceanographyGeochemistryTotal organic carbonSeawaterEnvironmental chemistryChemistryCalcite

Abstract

fetched live from OpenAlex

Abstract The Cretaceous Oceanic Anoxic Event 1a (Early Aptian) is thought to be causally related to the eruption of the Ontong Java Plateau large igneous province. This study uses osmium isotope records to quantify the magnitude of the respective CO 2 emissions up to the onset of Oceanic Anoxic Event 1a, and model the associated changes in carbonate saturation state (Ω), atmospheric pCO 2 , carbon isotope ratios and the carbonate compensation depth with a carbon cycle model. These model results suggest that volcanism associated with the rapid negative 187/188 osmium ratios observed during the onset of Oceanic Anoxic Event 1a (Selli Event) increased the planetary CO 2 degassing flux at least six‐fold, causing a negative δ 13 C excursion of ca 1·5‰ in the dissolved surface ocean inorganic carbon pool. This is consistent with previously published δ 13 C data. Volcanic degassing of this magnitude would also suppress the aragonite saturation state of surface water to near under‐saturated values (Ω ca 1·1 to 0·9), shoal the carbonate compensation depth by 1500 m and increase the atmospheric pCO 2 by 3000 p.p.m., before increased weathering and anoxia would counter the pCO 2 increase.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.301
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.256
Teacher spread0.232 · 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 teacher head, 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

Citations29
Published2016
Admission routes2
Has abstractyes

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