Icebreaking Ore Carrier Project for Baffinland Iron Mines Corporation
Bibliographic record
Abstract
Baffinland Iron Mines Corporation is planning to utilize the iron deposits on the northern Baffin Island (Canada). The iron ore was discovered in the beginning of 1960ies. The mine is 100-142km from the sea shore (Milne Inlet or Steensby Inlet). The sea area from Milne Inlet and Steensby Inlet to North Atlantic is most of the year ice covered. Open water period may be only three months, from July to October. The operation is planned to be year-round. The amount of iron ore to be transported in the beginning of the production in 2014 is c. 18 million tonnes/year. The ore carriers are to be operated independently without icebreaker assistance. The ore carriers are assumed to operate at full draught both in loaded and ballast condition when operating in ice. The ship size was selected to be of main dimensions as a Dunkirkmax/Capesize vessel. There are two basic ore carrier alternative designs; The first alternative is conventional icebreaking vessel, which mainly operates by breaking ice with the bow. The second alternative is the so called Double Acting Ship (DAS). In the DAS concept the vessel is designed to operate bow first most of the time, in open water and in light ice conditions, but in severe ice conditions running astern. This paper describes the design process of the vessels including the basic requirements, operational conditions, transit simulations, model tests and the vessel designs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".