Direct Monitoring Reveals Initiation of Turbidity Currents From Extremely Dilute River Plumes
Bibliographic record
Abstract
Abstract Rivers (on land) and turbidity currents (in the ocean) are the most important sediment transport processes on Earth. Yet how rivers generate turbidity currents as they enter the coastal ocean remains poorly understood. The current paradigm, based on laboratory experiments, is that turbidity currents are triggered when river plumes exceed a threshold sediment concentration of ~1 kg/m 3 . Here we present direct observations of an exceptionally dilute river plume, with sediment concentrations 1 order of magnitude below this threshold (0.07 kg/m 3 ), which generated a fast (1.5 m/s), erosive, short‐lived (6 min) turbidity current. However, no turbidity current occurred during subsequent river plumes. We infer that turbidity currents are generated when fine sediment, accumulating in a tidal turbidity maximum, is released during spring tide. This means that very dilute river plumes can generate turbidity currents more frequently and in a wider range of locations than previously thought.
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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) | 0.001 | 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".