Deep-Water Sediment Bypass
Bibliographic record
Abstract
Abstract: Submarine gravity flows are a key process for transporting large volumes of sediment from the continents to the deep sea. The location, volume, and character of the sediment bypassed by these flows dictates the areal extent and thickness of the associated deposits. Despite its importance, sediment bypass is poorly understood in terms of flow processes and the associated stratigraphic expression. We first examine the relationships between the physical parameters that govern bypass in flows, before assessing the variable stratigraphic expression of bypass from modern seafloor, outcrop, and subsurface datasets. Theoretical and numerical approaches distinguish grain size, slope, flow size, and sediment concentration as parameters that exert major controls on flow bypass. From field data, a suite of criteria are established to recognize bypass in the geological record. We identify four bypass-dominated zones, each of which is associated with a set of diagnostic criteria: slope-channel bypass, slope-bypass from mass wasting events, base-of-slope bypass, and basin-floor bypass. As the expression of bypass varies spatially and is dependent on the scale of observation, a range of scale-dependent criteria are required for robust interpretation of these zones in the field or subsurface. This synthesis of deep-water sediment bypass highlights the challenge in quantitatively linking process with product. The establishment of criteria to recognize sediment bypass, qualitatively linked with flow processes, is an important step towards improving our understanding of submarine flow dynamics and resultant stratigraphic architecture.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".