The Response of Spit Shapes to Wave-Angle Climates
Bibliographic record
Abstract
We investigate spit formation and evolution in light of the high-wave-angle instability in shoreline shape arising from a maximizing angle for wave-driven alongshore sediment transport. Single spits emerge in a simple one-contour line numerical model that evolves the coast using morphodynamic feedbacks and a `climate' of waves approaching the shore from variable directions. Analysis of sediment transport and shoreline stability metrics illustrate how spits can be generated, demonstrating how waves from all angles can play a role in spit formation and evolution. Simulations suggest that regardless of whether high- or low-angle waves dominate relative to the general shoreline trend, as spits extend offshore, they tend to orient themselves such that most of their coast barely experiences low-angle waves and alongshore sediment transport to the spit end is maximized. This `graded' spit shape minimizes gradients in sediment flux, while the recurve at the spit end experiences larger gradients and a region of high-angle instability. Examining hindcast wave data, similar trends are seen along the natural example of Long Point, Lake Erie, Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".