Field evidence for coal combustion links the 252 Ma Siberian Traps with global carbon disruption
Bibliographic record
Abstract
Abstract The Permian-Triassic extinction was the most severe in Earth history. The Siberian Traps eruptions are strongly implicated in the global atmospheric changes that likely drove the extinction. A sharp negative carbon isotope excursion coincides within geochronological uncertainty with the oldest dated rocks from the Norilsk section of the Siberian flood basalts. We focused on the voluminous volcaniclastic rocks of the Siberian Traps, relatively unstudied as potential carriers of carbon-bearing gases. Over six field seasons we collected rocks from across the Siberian platform, and we show here the first direct evidence that the earliest eruptions in the southern part of the province burned large volumes of a combination of vegetation and coal. We demonstrate that the volume and composition of organic matter interacting with magmas may explain the global carbon isotope signal and may have significantly driven the extinction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".