Ebullition‐enhanced solute transport in coarse‐grained sediments
Bibliographic record
Abstract
Pore‐water exchange caused by ebullition of small oxygen bubbles produced by microalgae in the surface layer of sand sediment at St. Joseph Bay (SJB), Gulf of Mexico, was contrasted with ebullition of larger methane bubbles generated by archaea in deeper layers of sub‐littoral sands at Hel Peninsula (HEL), Baltic Sea. At SJB, ebullition of O2‐enriched bubbles in August 2011 averaged 225 ± 132 mL m−2 d−1, and at a mean bubble diameter of 1.0 ± 0.3 mm, up to 516,000 bubbles m2−2 d−1 were released from the upper 10 mm of sediment. Ebullition of CH4‐enriched bubbles at HEL reached 907 ± 278 mL m2−2 d2−1 in August 2003, with bubbles of 10–20 mm diameter ascending from > 100 mm sediment depth at a rate of up to 210 bubbles m−2 d−1. In situ chamber experiments showed that ebullition of 12 mm diameter bubbles from 80 mm sediment depth at a rate of ~ 5 mL min−1 (254 L m−2 d−1) enhanced interfacial fluid flux ~ three‐fold compared to chambers with no ebullition. In contrast, release of 2 mm diameter bubbles from 3 mm sediment depth at a lower rate of ~ 1 mL min−1 increased interfacial flux about 21‐fold in laboratory tests, revealing that frequent ebullition of small bubbles released near the sediment surface enhances sediment‐water fluid flux more effectively than ebullition of larger bubbles ascending from deeper sediment depths at low frequency. Particle image velocimetry showed that bubble ebullition effectively entrained pore fluid into the turbulent boundary layer, thereby enhancing benthic pelagic coupling.
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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 | 0.000 |
| 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) | 0.000 | 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".