Fluid seepage velocities through marine sediments constrained by a global compilation of interstitial water SO<sub>4</sub><sup>2−</sup>, Mg<sup>2+</sup>, and Ca<sup>2+</sup> profiles
Bibliographic record
Abstract
Abstract The depth dependence of the SO42−, Mg2+, and Ca2+ contents of interstitial waters extracted from sediments in 140 Deep Sea Drilling Project/Ocean Drilling Program/Integrated Ocean Drilling Program drill holes on oceanic crust has been fit using a model of transport (advection and diffusion) and reaction. These drill holes come from a range of crustal ages, sediment types, sediment thicknesses, and sediment accumulation rates. The best fitting specific discharge through the sediment at these locations is estimated to be generally <500 m Myr−1 (0.05 cm yr−1), where sediments are thicker than 100 m, although an order of magnitude faster seepage is estimated for some locations with sediment tens of meters thick. Assuming that the drill holes are globally representative, then seepage of fluids through marine sediments at specific discharges of a few hundred m Myr−1 is estimated to be only a few percent of the total ridge flank hydrothermal fluid flux. This is consistent with the previous suggestion that hydrothermal fluid exchange between the ocean and the crustal aquifer primarily occurs through basement outcrops. Chemical fluxes of SO42−, Mg2+, and Ca2+ across the sediment‐water interface globally (excluding continental margins) are estimated to be less than 10% of the riverine input to the ocean.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".