Bibliographic record
Abstract
Wetlands include mangroves, peatlands and marshes, rivers and lakes, deltas, floodplains, rice fields, and even coral reefs. It is known that wetlands are ecologically sensitive systems and the most vulnerable of habitats. Anthropogenic activities (urbanization, water uses, land cover changes, industrial activity, pollution, climatic change, etc.) have direct and indirect effects on wetlands. The evaluation of wetlands with a multidisciplinary perspective in environmental sciences and social sciences provides efficient results. Each chapter takes a crucial look at different approaches to the solution by analyzing wetland problems in the laboratory or in the field and collecting data. The purpose of this book is to help researchers, scientists, and decision-makers utilize a methodology appropriate for a specific problem.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.025 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.058 |
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; both teacher heads agree on what is shown here.
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".