Randle Reef Sediment Remediation Project
Bibliographic record
Abstract
The Randle Reef site is the largest coal tar-contaminated sediment site in the Great Lakes. This paper presents a summary of the design for the Randle Reef Remediation Project, which involves dredging 500,000 cubic meters (654,000 cubic yards) of sediment and construction of a 7.5-hectare (18.5-acre) Engineered Containment Facility (ECF) for containment of the dredged material. Contaminants of concern are polycyclic aromatic hydrocarbons (PAHs), as well as metals and coal-tar nonaqueous-phase liquid (NAPL). The ECF will serve to isolate contaminated sediment beneath the containment facility and dredged from the Harbour and will provide new land for a near-shore island terminal and provide berths for deep draft vessels. A multi-layer cap will be constructed over the dredged material placed in the ECF. The remediation project includes many design elements which are summarized in this paper. Construction is anticipated to begin in 2014/15.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".