Thirty years of sediment–water science: history, trends and future directions
Bibliographic record
Abstract
In 1976, an interdisciplinary group of international researchers met in Amsterdam to share their knowledge about sediment–water interactions, and subsequently formed the International Association for Sediment Water Science (IASWS). Since then, IASWS has met tri-annually at a variety of locations throughout the world. Over the last 30 years, over 1000 oral presentations have been presented at IASWS symposia, more than half of which have been published as books or special issues of scientific journals. As such, the publications provide an excellent record of developments in the field of sediment–water interactions over the last 30 years. This paper provides an overview of the history of the Association, and a qualitative and quantitative content analysis of the IASWS publications. Changing patterns of research in some of the dominant symposia themes, including sediment-associated nutrients, contaminants and metals as well as sediment dynamics and material cycling are presented. Temporal changes in the investigative scale of published studies and an eventual increase in papers addressing management considerations were observed. Potential directions for the future of IASWS and some directives for ensuring that future research informs aquatic ecosystem health are suggested.
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 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.020 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".