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Record W1999052439 · doi:10.1073/pnas.1118675109

Explosive eruption of coal and basalt and the end-Permian mass extinction

2011· article· en· W1999052439 on OpenAlexaboutno aff
D. E. Ogden, Norman H. Sleep

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsFlood basaltBasaltPermian–Triassic extinction eventGeologyGeochemistryExtinction eventCarbonateEarth sciencePaleontologyTectonicsChemistryVolcanism

Abstract

fetched live from OpenAlex

The end-Permian extinction decimated up to 95% of carbonate shell-bearing marine species and 80% of land animals. Isotopic excursions, dissolution of shallow marine carbonates, and the demise of carbonate shell-bearing organisms suggest global warming and ocean acidification. The temporal association of the extinction with the Siberia flood basalts at approximately 250 Ma is well known, and recent evidence suggests these flood basalts may have mobilized carbon in thick deposits of organic-rich sediments. Large isotopic excursions recorded in this period are potentially explained by rapid venting of coal-derived methane, which has primarily been attributed to metamorphism of coal by basaltic intrusion. However, recently discovered contemporaneous deposits of fly ash in northern Canada suggest large-scale combustion of coal as an additional mechanism for rapid release of carbon. This massive coal combustion may have resulted from explosive interaction with basalt sills of the Siberian Traps. Here we present physical analysis of explosive eruption of coal and basalt, demonstrating that it is a viable mechanism for global extinction. We describe and constrain the physics of this process including necessary magnitudes of basaltic intrusion, mixing and mobilization of coal and basalt, ascent to the surface, explosive combustion, and the atmospheric rise necessary for global distribution.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

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 studies0.0000.003
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 head0.051
GPT teacher head0.254
Teacher spread0.202 · 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.

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

Citations80
Published2011
Admission routes1
Has abstractyes

Explore more

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