Can We Engineer Ice Rubble for Protection of Offshore Platforms in the Beaufort Sea
Bibliographic record
Abstract
The objective of this four-year study was to evaluate and develop methods of engineering ice rubble to reduce loads on offshore structures. Numerous questions needed to be addressed, not the least of which were: "Is it worthwhile?", "Is it practical?", and "What will it cost?" This paper provides an overview description of the work done for the project. The conclusions were that for situations where a caisson-type structure is located in a region of weak, cohesive soil, generating ice rubble through the use of Ice Rubble Generators (IRGs) was both practical (reducing ice loads on the structure and extending the range of loading that the structure could encounter) and economical (a significant reduction in structure cost, despite the additional costs of the IRGs, depending on the location). The IRGs also had added benefits with respect to reducing ice loading due to potential Multi-Year Ice incursions in the summer. The results indicate that IRGs are an additional design option as part of the development of offshore production structures in the American and Canadian Beaufort Seas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".