Microbial Induced Corrosion on a Wharf in the Canadian Arctic
Bibliographic record
Abstract
The Nanisivik wharf was constructed by the Government of Canada in Strathcona Sound in 1975, on Northern Baffin Island, in the Canadian Arctic. The port facility serviced a nearby lead-zinc mine until the mine ceased production in 2002 and began mine decommissioning in the following years. In 2008, the Government of Canada began planning the reuse of the port facility, including the wharf, as a new refuelling station for planned new Arctic patrol ships that would be operated by the Department of National Defence (DND). The wharf structure is of conventional Arctic deep sea wharf construction, comprising steel sheet pile cells and the first comprehensive inspection of the structure commissioned by the DND was completed in 2010. The inspection revealed several issues that would need to be addressed to allow the wharf to be operated for the further 50 years mandated by the new operations. In particular, microbiological and molecular biological investigations performed during the inspection revealed that the sheet piles were being aggressively attacked by bacterial activity. The corrosion was found to be anaerobic corrosion carried out by sulfate reducing bacteria (SRB) in co-activity with sulfur oxidizing bacteria (SOB). Microbial Induced Corrosion (MIC) was already suspected prior to the 2010 inspection based on photographic evidence dating as far back as 1985 and from comments reported after a brief inspection of the wharf in 2008. Comprehensive thickness measurements made in 2010 confirm that the corrosion rates are increasing and that MIC, if left unchecked, could render the structure inoperable in as early as 10 years time. This paper discusses the results of the MIC studies and some of the rehabilitation options considered to address the MIC issues.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".