Bibliographic record
Abstract
This new publication reviews recent advances in contaminated sediments-management-related research and focuses on the engineering aspects of contaminant transport, erosion, stability, monitoring, and modeling. It identifies both established and innovative physico-chemical and biological tests and methods used to characterize and evaluate properties and behavior of contaminated sediments, as well as the potential for contaminant transfer. This data reflects recent work carried out on large coastal investigations and on natural and artificial capping of contaminated sediments. Twenty-three peer-reviewed papers cover: Sediment Characterization of contaminated sediments has become more and more complex. It involves ex situ techniques from standard tests (e.g., physical properties) to biological analysis in addition to all the chemical analyses, but also in situ ones like erodability tests. Mitigation and Restoration Methods are diversified and touch on many different environments from river sediments and harbor lagoons to land reclamation. They involve techniques ranging from the use of geotextiles and geocomposites to selective sequential extraction methods Monitoring and Performance aspects of contaminated sediments are largely supported by extensive site investigations, like the Southern California project, but also by the development of modeling tools. In addition, four peer-reviewed papers in this volume summarize a five-year research effort aimed at evaluating the performance of a catastrophic capping layer resulting from the major 1996 Saguenay flood disaster that proved to be very beneficial to the Saguenay Fjord environment and ecosystem by covering most of the ancient contaminated sediments. Audience: This book is an invaluable resource for environmental engineers and scientists, water quality engineers, soil scientists, geotechnical engineers, and environmentalists, educators, and legislators.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.852 | 0.838 |
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; the direct Gemma label and the distilled Codex classifier 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".