Assessment of Totally Enclosed Propelled Survival Craft (TEMPSC) hull design performance in ice covered waters
Bibliographic record
Abstract
Hazards in offshore operation, such as gas leak, explosions, fires, collisions and icebergs, could result in emergencies that necessitate abandon of the platform. These emergencies could arise in calm water, during a storm or in pack ice. Therefore, evacuation system performance must be assessed in a wide range of weather conditions in wind, waves and ice. The focus in this report is lifeboat performance in pack ice. Lifeboats are often used as one of the secondary means of evacuation. In the east coast ofCanada and in different parts of the world, broken ice is a common occurrence. Pack icecan surround an offshore platform or a vessel. If abandonment of a platform or a vessel iswarranted, then the lifeboat may need to be able to travel through ice to a safe areabeyond the hazardous area boundary to escape dangers such as toxic fumes and smoke. There are many factors that affect TEMPSC performance in ice, including iceconcentration, ice thickness, ice strength, ice floe size etc. The speed and navigability ofthe craft are expected to deteriorate with worsened ice conditions. It is important in the evaluation of evacuation systems and in the preparation of anemergency preparedness plan that these factors are taken into account. Therefore, it isessential to investigate how lifeboat performance can be limited by different iceconditions. If the performance of lifeboats is inadequate for the expected operatingenvironmental conditions, consideration needs to be given to complement them withother means of evacuation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".