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Record W2586630649 · doi:10.1073/pnas.1610931114

Redox chemistry changes in the Panthalassic Ocean linked to the end-Permian mass extinction and delayed Early Triassic biotic recovery

2017· article· en· W2586630649 on OpenAlexafffundabout
Guijie Zhang, Xiaolin Zhang, Dongping Hu, Dandan Li, Thomas J. Algeo, James Farquhar, Charles M. Henderson, Liping Qin, Megan Shen, Danielle Shen, Shane D. Schoepfer, Kefan Chen, Yanan Shen

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsUniversity of Calgary
FundersHigher Education Discipline Innovation ProjectNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesNational Science Foundation
KeywordsExtinction eventPermianPermian–Triassic extinction eventPaleontologyEarly TriassicExtinction (optical mineralogy)RedoxGeologyOceanographyChemistryOrganic chemistryDemography

Abstract

fetched live from OpenAlex

Significance To understand how most life on Earth went extinct 250 million years ago, we used multiple sulfur isotopes to investigate redox chemistry changes in the Panthalassic Ocean, comprising ∼85–90% of the contemporaneous global ocean. The S-isotopic anomalies from Canada and Japan provide evidence for the timing of the onset of euxinia and mixing of sulfidic and oxic waters. Our data suggest that shoaling of H 2 S-rich waters may have driven the mass extinction and delayed the recovery of the marine ecosystem. This study illustrates how environmental changes could have had a devastating effect on Earth’s early biosphere, and may have present-day relevance because global warming and eutrophication are causing development of sulfidic zones on modern continental shelves, threatening indigenous marine life.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.093
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.038
GPT teacher head0.270
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

Citations83
Published2017
Admission routes3
Has abstractyes

Explore more

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