Quantifying the process and abruptness of the end-Permian mass extinction
Bibliographic record
Abstract
Studies of the end-Permian mass extinction have suggested a variety of patterns from a single catastrophic event to multiple phases. But most of these analyses have been based on fossil distributions from single localities. Although single sections may simplify the interpretation of species diversity, they are susceptible to bias from stratigraphic incompleteness and facies control of preservation. Here we use a data set of 1450 species from 18 fossiliferous sections in different paleoenvironmental settings across South China and the northern peri-Gondwanan region, and integrate it with high-precision geochronologic data to evaluate the rapidity of the largest Phanerozoic mass extinction. To reduce the Signor-Lipps effect, we applied constrained optimization (CONOP) to search for an optimal sequence of first and last occurrence datums for all species and generate a composite biodiversity pattern based on multiple sections. This analysis indicates that an abrupt extinction of 62% of species took place within 200 Kyr. The onset of the sudden extinction is around 252.3 Ma, just below Bed 25 at the Meishan section. Taxon turnover and diversification rates suggest a deterioration of the living conditions nearly 1.2 Myr before the sudden extinction. The magnitude of the extinction was such that there was no immediate biotic recovery. Prior suggestions of highly variable, multi-phased extinction patterns reflect the impact of the Signor-Lipps effect and facies-dependent occurrences, and are not supported following appropriate statistical treatment of this larger data set.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".