Bibliographic record
Abstract
[1] Temporal variation in the geometric roughness of the mobile sandy seabed during wave forcing events is investigated as a function of bed state. The bed states include irregular ripples, cross ripples, linear transition ripples, and flat bed, each appearing repeatedly within a different range of wave energies, as part of the bed state storm cycle. Ripple wavelengths determined from ensemble-averaged roughness spectra indicate that irregular and cross ripples are suborbital, whereas linear transition ripples are anorbital. The observed ripple steepnesses indicate that irregular and linear transition ripples fall slightly below Nielsen's (1981) field data relation, whereas cross ripple steepnesses are anomalously low in comparison. Time series of geometric roughness are coherent across spatial frequency. Abrupt changes in geometric roughness occurred on timescales of ∼3 h on average during both the onset and the waning stages of storm events: i.e., for both decreasing and increasing roughness, respectively. Predicted response times, based on ripple volume and bed load transport rate, are in agreement with the observations when the best fit form of the Meyer-Peter and Müller (1948)-type bed load relation obtained by Ribberink (1998) is used. In contrast, the more standard form of this relation and the associated parameters yield predicted response times much shorter than those observed.
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 | 0.001 |
| 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".