Global Ocean Sediment Composition and Burial Flux in the Deep Sea
Bibliographic record
Abstract
Abstract Quantitative knowledge about the burial of sedimentary components at the seafloor has wide‐ranging implications in ocean science, from global climate to continental weathering. The use of 230 Th‐normalized fluxes reduces uncertainties that many prior studies faced by accounting for the effects of sediment redistribution by bottom currents and minimizing the impact of age model uncertainty. Here we employ a recently compiled global data set of 230 Th‐normalized fluxes with an updated database of seafloor surface sediment composition to derive atlases of the deep‐sea burial flux of calcium carbonate, biogenic opal, total organic carbon (TOC), nonbiogenic material, iron, mercury, and excess barium (Ba xs ). The spatial patterns of major component burial are mainly consistent with prior work, but the new quantitative estimates allow evaluations of deep‐sea budgets. Our integrated deep‐sea burial fluxes are 136 Tg C/yr CaCO 3 , 153 Tg Si/yr opal, 20Tg C/yr TOC, 220 Mg Hg/yr, and 2.6 Tg Ba xs /yr. This opal flux is roughly a factor of 2 increase over previous estimates, with important implications for the global Si cycle. Sedimentary Fe fluxes reflect a mixture of sources including lithogenic material, hydrothermal inputs and authigenic phases. The fluxes of some commonly used paleo‐productivity proxies (TOC, biogenic opal, and Ba xs ) are not well‐correlated geographically with satellite‐based productivity estimates. Our new compilation of sedimentary fluxes provides detailed regional and global information, which will help refine the understanding of sediment preservation.
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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) | 0.001 | 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 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".