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Record W7119356961

New U–Pb Geochronology for the Central Atlantic Magmatic Province, Critical Reevaluation of High-Precision Ages and Their Impact on the End-Triassic Extinction Event

2023· article· en· W7119356961 on OpenAlexaboutno aff

Bibliographic record

VenueScholar Works (Boise State University) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSillDikeZirconIgneous rockGeochronologyExtinction eventSedimentary rockEvent (particle physics)
DOInot available

Abstract

fetched live from OpenAlex

The end-Triassic extinction (ETE) event represents one of the ‘big five’ episodes of mass extinction. The leading hypothesis for the cause of the ETE is the intrusion of voluminous magmas of the Central Atlantic Magmatic Province (CAMP) into carbon-rich sediments of two South American sedimentary basins, around 201.5 Ma. The timing of dikes and sills emplacement, however, must be considered in light of age models from CAMP rocks occurring in North America. In this work, we present new high-precision ages for critical samples in NE Brazil (201.579 ± 0.057 Ma) and Canada (201.464 ± 0.017 Ma), in order to evaluate how the South and North American magmatic events compare at the 100-ka level, and to the ETE timing. We also discuss inter-laboratory reproducibility of high-precision CAMP ages, including the 230Th disequilibrium corrections that are made to zircon U–Pb dates. Our findings in this newly discovered extension of the CAMP large igneous province in NE Brazil support the hypothesis that the CAMP may be responsible for the ETE through the triggering of greenhouse gas release from magma-evaporite interactions (contact metamorphism) in the South American basins.

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)0.001
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 score0.139
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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