Iceberg Risk Analysis for Strait of Belle Isle Cable Crossing
Bibliographic record
Abstract
Abstract In 2016 Nalcor Energy installed subsea cables across the Strait of Belle Isle, which comprises part of the Lower Churchill Transmission Project linking Muskrat Falls, Labrador, and Soldier's Pond, Newfoundland. The cable crossing site is southwest of a shoal which filters out deeper draft icebergs which could potentially contact and damage the cable. An initial study in 2011 was followed by iceberg tracking and current monitoring programs at the cable crossing site and a final study incorporating these data 2015-2016. This paper describes the application of a drift-based Monte Carlo model to assess iceberg risk to cables laid on the seabed in the Strait of Belle Isle. The model considers the effect of iceberg rolling which could potentially result in icebergs increasing draft and contacting cables laid on the seabed. Modeled iceberg drift was based on field observations, and measured and modeled currents. Based on results from the 2011 analysis it was decided to use directional drilling to route the initial portions of the cable from shore to break-put locations on the seabed in water depths in excess of 70 m. Rock dumping is used to stabilize the cables on the seabed at deeper water depths. Due to the extreme difficulties in trenching the very strong seabed or tunneling across the Strait of Belle Isle, the selected solution offers the most technically feasible and cost-effective solution for cable routing across the Strait of Belle Isle.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".