Long-term history of continental weathering and particle transport to the sea
Bibliographic record
Abstract
Here, we explore the long-term history of chemical weathering and particle transport from the continents to the oceans by leveraging the histories of Zr/Al, Rb/Al, and Na/Al in marine sediments over the last 2000 My. We interpret these data in the context of elemental behavior in modern weathering environments and modern marine sediments. We find that from 2000 Mya to ca. 650 Mya, physical erosion was effective, where braided rivers efficiently delivered particles from land to the sea. Overall, chemical weathering was less efficient than now, although many easily weatherable minerals were as weathered as today. We suggest a dramatic change in weathering dynamics after 650 Mya when modern-like deep subduction originated. With this development, mantle dynamics, by promoting periodic vigorous subduction and intense mountain building, began to control the intensity of chemical weathering and particle transport to the oceans. Through spectral analysis of several geochemical records, we find that during times of enhanced subduction and mountain building, continents underwent periods of net erosion and less intense chemical weathering, while during periods of less intense subduction, continents accumulated particles, and chemical weathering was more intense. The evolution and proliferation of land plants changed chemical weathering intensity but had little apparent impact on the cyclic nature of particle transport and storage on the continents. These results could offer a framework to better understand the evolution of elemental cycling from the continents to the oceans over the last 2000 My.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".