The dynamics of global change at the <scp>P</scp>aleocene‐<scp>E</scp>ocene thermal maximum: A data‐model comparison
Bibliographic record
Abstract
Abstract We integrate published stable isotopic, chemical, mineralogical, and biotic data from the onset of the Paleocene‐Eocene thermal maximum (PETM) at Site 690, Maud Rise in the Southern Ocean. The integrated data set documents a sequence of environmental steps including warming of the ocean from the surface downward, and modification of its thermal and nutrient structure, acidification of the deep ocean, and the onset of continental weathering. The age of the events with respect to the onset of the PETM is calibrated with three different age models. The relative and absolute timing of the steps are compared with simulated temperature, salinity, calcite saturation, and dissolved PO4 and O2, at different depths in the ocean, generated with the UVic Earth System Climate Model of intermediate complexity. The simulation supports the top to bottom transfer of heat and carbon, and generally agrees with age models in terms of the durations of leads and lags in temperature, C‐isotope, and biotic responses. Moreover, the simulation shows that stratification increased and the nutricline strengthened at the onset of the PETM. These environmental changes explain the abundance of deep‐dwelling nannoplankton and foraminifera during the early part of the event. The modeled calcite saturation is consistent with a harsh deep‐sea habitat at the time of the benthic foraminiferal extinction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".