Formation and dynamics of an ice bustle at the Nanisivik Wharf
Bibliographic record
Abstract
In the summer of 2015, the Department of National Defense’s began construction of a new deep water refueling station in Nanisivik In October of 2017, two load panels were installed on the outward face of one of three cylindrical cells making up the wharf. In June of 2018, a field team performed a short measurement program to validate the pressure panels and data logger, extract data, and collect measurements of the ice developed during the previous winter. A region of very thick ice first year sea ice in an ‘active zone’ develops around the wharf every winter. The thickness of the ice bustle and surrounding level ice was measured manually via ice auguring and an elevation survey work at the time of the June 2018 field visit. The ice feature was found to be roughly 4-5m thick on average, and the parent level ice was recorded in the range of 1.6-1.9m. The motions of the active zone were monitored via a 6 degree of freedom position tracking system throughout a full tide cycle to identify early melt-season dynamics of the ice feature. Motions of the ice in the active zone are compared with tide information demonstrating a strong dependence. The active zone ice feature forms initially from an ice bustle, ad-frozen to the wharf. The life cycle of the ice bustle and a summary of the various dynamics observed both through the measurement program and the loading records are discussed, with particular emphasis on the transition from an ad-frozen ice feature, affixed to the wharf, to a free floating bustle. A region of hard ice appeared to have formed on the steel sheet piles encasing the wharf during the spring. The impact on pressures exerted on the wharf is presented and discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".