ASSESSING THE DYNAMIC RESILIENCE OF NEWLY ESTABLISHED SALT MARSHES TO WAVE-INDUCED STRESS OVER TIME
Bibliographic record
Abstract
Restoration of coastal salt marshes has become progressively more common as the ecosystem services provided by these systems, including flood protection and shoreline stabilization, have been acknowledged. Recent examples in Canada include a marsh restoration in Boundary Bay (British Columbia) and a managed realignment at Belcher Street (Nova Scotia) (van Proosdij et al., 2023). To date, most laboratory-based live vegetation experiments have used transplanted natural marshes (Möller et al., 2006; Maza et al., 2022), which are representative of established marsh conditions. However, seasonal fluctuations in biomass and the reduced density of newly established (constructed) marshes compared to their natural counterparts (Tempest et al., 2015) can potentially result in significant variability in performance. There is a pressing need to understand the performance of newly established marshes to better characterize short- term benefits and ensure the long-term viability of these restoration efforts.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".