Phase 1 Esquimalt Graving Dock Waterlot Remediation
Bibliographic record
Abstract
The Esquimalt Graving Dock (EGD) is located on federal Crown-owned property in Esquimalt Harbour on Vancouver Island, British Columbia, and is managed by the federal custodian Public Works and Government Services Canada (PWGSC). The EGD facility has been operating for the repair and maintenance of military and civilian vessels since 1927, and it is the largest solid-bottom commercial dry dock on the West Coast of the Americas. Historical contamination includes a broad range of chemicals, such as metals, polychlorinated biphenyls (PCBs), tributyltin (TBT), and polycyclic aromatic hydrocarbons (PAHs). In support of objectives of the Federal Contaminated Sites Action Plan (FCSAP), as well as a potential governance change of the EGD facility, PWGSC developed a multi-phase remedial action plan for cleaning up contaminated sediments in and adjacent to the EGD waterlot. Phase 1A was completed in 2013 and included installation of a sheetpile perimeter wall around the existing timber jetty structures to prevent re contamination of remediated sediments during subsequent phases of the project. Phase 1B was completed in March 2014 and included 144,000 cubic metres (m3) of remedial dredging and off-site upland disposal of contaminated sediments, placement of approximately 24,000 m3 of in-water slope armour, and placement of residuals management cover (RMC) over approximately 74,000 square metres. This paper discusses the key challenges encountered during the Phase 1B remedial design, contracting, and construction, including development of the dredge design, residuals management approach, accommodating highly variable operational needs into the construction sequencing approach, developing contract documents to account for local contractor experience, and specific elements that presented a challenge during construction.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".