Deformation of <i>Spartina patens</i> and <i>Spartina alterniflora</i> stems under irregular wave action
Bibliographic record
Abstract
Physical modeling studies have endeavored to quantify the influence of plant biophysical parameters and hydrodynamics on wave-vegetation interactions and coastal protection. The accuracy with which such studies have characterized stem motion is limited by the predominant use of plant surrogates, and the few saltmarsh species considered in live vegetation studies. To address this, prototype-scale experiments were conducted in the outdoor Large Wave Canal of the Institut National de la Recherche Scientifique, Québec, in collaboration with the University of Ottawa and the National Research Council Canada, allowing novel characterization of live vegetation deformation under wave action. Two saltmarsh species were investigated (Spartina alterniflora, Spartina patens) under various irregular wave conditions (0.03 m< Hs <0.28 m, Ts ≈ 2.5, 10 s). Stem deformation was characterized using submerged cameras and bending angle tracking, coupled with wave height and velocity measurements. Significant differences in stem flexibility were observed between species, with S. alterniflora exhibiting more rigid stems (EIalterniflora=0.051 Nm2) than S. patens (EIpatens=0.0015 Nm2; t-test; p<0.05). The two species consequexhibited different bending angles under similar hydrodynamic conditions, expected to influence their relative coastal protection capacity. These findings provide critical insight into the design of marsh construction or restoration for coastal protection.
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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 | 0.000 | 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".