The wave dissipation potential of Spartina alterniflora in the Bay of Fundy
Bibliographic record
Abstract
The purpose of this research is to determine the wave dissipation potential of salt marsh vegetation in a temperate, hypertidal estuary.The study site is Clifton Marsh, Nova Scotia, in the Bay of Fundy.This site was selected in part because it is monospecific, with Spartina alterniflora.This research will investigate how effective Spartina alterniflora is at attenuating wave energy and the variability in wave height as the vegetation height increases over time.A transect was set up with 4 RBRduet3 T.D|wave16temperature and pressure loggers extending from the mudflat to the vegetated section.Data were collected from mid June to early December 2020.For each two-week dataset, the data was sorted to include only that with a depth greater than 0.1 m, and events were selected to have a significant wave height that is greater than 0.05 m.Vegetation surveys were carried out biweekly to measure the various parameters such as the stem height, stem diameter and the width of the middle top parts of the leaves.The outcomes show that vegetation has an effect on the wave energy and significant wave height and affects the attenuation capacity of salt marshes.This research demonstrates that the presence of vegetation on salt marshes plays an important role in wave dissipation and attenuation.There needs to be a better understanding of vegetated intertidal environments and incoming waves, to achieve sustainable coastal management and planning.
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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 | 0.001 | 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".