Contaminated Sediment Management: the Canadian Experience
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 Since the beginning of North America's industrialization, the Great Lakes have been negatively impacted by the discharge of industrial, agricultural and municipal pollutants. The governments of Canada and the United States have recognized that the accumulation of pollutants within the bottom sediment and the water column has had a detrimental effect on the Great Lakes ecosystem. In 1972, Canada and the United States signed the Great Lakes Water Quality Agreement, which established common water quality objectives and commitments to programs and other measures to achieve these objectives. This included measures for the abatement and control of pollution from dredging activities. By 1985, the International Joint Commission, a body established by the two countries to provide advice on boundary water issues, identified 43 Areas of Concern where impaired water quality prevented full beneficial use of rivers, bays, harbours and ports. The Great Lakes Water Quality Agreement, amended in 1987, committed both countries to concentrate remediation efforts in these 43 Areas of Concern. This led to the development of Remedial Action Plans to assess and remediate contamination problems. Contaminated sediment was identified in all of these Areas of Concern. In 1989, the Canadian government created the 5-year $125-million Great Lakes Action Plan in support of the Great Lakes Water Quality Agreement. Of this, $55 million was allocated to the Great Lakes 2000 Cleanup Fund for the 17 Canadian Areas of Concern. A portion of the Cleanup Fund was designated for the development and demonstration of technologies for assessment, removal and treatment of contaminated sediment. Since its creation, the Remediation Technologies Program, established under the Cleanup Fund, has successfully performed 3 full-scale remediation projects, 11 pilot-scale technology demonstrations and 29 bench-scale tests. In addition to these projects, the program also evaluated existing sediment management practices and processes.
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 | 0.008 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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