Which Triggers Produce the Most Erosive, Frequent, and Longest Runout Turbidity Currents on Deltas?
Bibliographic record
Abstract
Abstract Subaerial rivers and turbidity currents are the two most voluminous sediment transport processes on our planet, and it is important to understand how they are linked offshore from river mouths. Previously, it was thought that slope failures or direct plunging of river floodwater (hyperpycnal flow) dominated the triggering of turbidity currents on delta fronts. Here we reanalyze the most detailed time‐lapse monitoring yet of a submerged delta; comprising 93 surveys of the Squamish Delta in British Columbia, Canada. We show that most turbidity currents are triggered by settling of sediment from dilute surface river plumes, rather than landslides or hyperpycnal flows. Turbidity currents triggered by settling plumes occur frequently, run out as far as landslide‐triggered events, and cause the greatest changes to delta and lobe morphology. For the first time, we show that settling from surface plumes can dominate the triggering of hazardous submarine flows and offshore sediment fluxes.
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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 | 0.000 |
| 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) | 0.001 | 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".