Nature-based solutions for coastal protection in the southern Caribbean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT The coastal shores of Trinidad and Tobago are at high risk (69.5 and 42.7%, respectively) of inundation from storm surges, sea level rise, and coastal erosion. The impacts of these coastal processes are predicted to worsen with climate change. Nature-based solutions utilizing the planting and rehabilitation of mangroves and seagrass beds are proposed. Sustainable green-engineered coastal protection strategies are pertinent for the low-lying coastal regions, as they house 70% of the country's population and roughly 80% of its socio-economic activity. Such measures offer ecological, environmental, social, and economic benefits, not provided by grey engineering, or concrete structures. Nature-based solutions are limited by anthropogenic factors, biotic/abiotic factors, data gaps, legal constraints, and social trends. These have resulted in declines in mangrove and seagrass bed coverage. A more sustainable coastal protection strategy using mangroves and seagrasses can be achieved by addressing these limitations and systematically utilizing various coastal ecological species. Building capacity, community building and outreach, and revising legal approaches and policing measures are necessary to maximize the benefits mangroves and seagrass beds offer as coastal protection measures.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it