Cost‐Effective Sediment Dredge Disposal Options for Small Craft Harbors in Canada
Bibliographic record
Abstract
Abstract Sediment dredge disposal options were reviewed to improve cost‐effectiveness and environmental safety for dredging of coastal sediments at the Department of Fisheries and Oceans Small Craft Harbours (DFO‐SCH) program in Canada. Historically, contaminated dredge sediments exceeding federal guidelines were disposed of in nearby landfills. Recent federal regulatory changes in sediment quality guidelines adopted by provincial regulators in Canada has resulted in updates to guidelines for disposal of contaminated solids in landfills. Updates now require specific and general disposal options for contaminated dredge material destined for land‐based disposal, resulting in more expensive disposal in containment cells (if contaminated sediments exceed federal guidelines). However, as part of this study, a leachate testing method was applied to contaminated sediments to simulate migration of potential contaminants in groundwater. Using this approach, leachate quality was compared to federal freshwater criteria and drinking water quality guidelines for compliance with new regulations. Leachate testing performed on the highest sediment contaminant concentrations triggered less than 2 percent potable water exceedances, meaning that most dredge spoils could be disposed of in privately owned or provincially operated landfill sites, providing less expensive disposal options compared to containment cell disposal. Current dredge disposal practices were reviewed at 35 harbor sites across Nova Scotia and their limitations identified in a gap analysis. Improved site management was developed following this review and consultation with interested marine stakeholders. New disposal options and chemical analyses were proposed, along with improvements to cost efficiencies for management of dredged marine sediments in Atlantic Canada. © 2013 Wiley Periodicals, Inc.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".