Model testing of an evacuation system in ice-covered water with waves
Bibliographic record
Abstract
A series of laboratory testing programs have been carried out to study the navigability of a conventional lifeboat design in a variety of environmental conditions. The present test series investigated the combined effects of ice and waves on this lifeboat design. The model lifeboat was constructed at a scale of 1:13. The variables in the test program included ice concentration, wave period and launch direction. The lifeboat had to meet a pass/fail criterion, which depended on whether the vessel could make way in a given environmental condition. Overall, the lifeboat was able to make way in all cases when traveling with the wave direction. Traveling into the waves, however, the vessel rarely made head way except in very light ice conditions. Compared to a previous test series with ice but no waves, the lifeboat was able to travel through higher ice concentrations when waves were present, compared to when there were no waves (as long as the vessel was traveling with the waves). Additionally, the vessel had a number of major problems,including lifeboat navigational break-downs due to ice becoming jammed in the propellers, the vessel becoming beached upon ice floes and poor visibility with respect to navigation using the onboard window. The ice floe collisions that the vessel encountered were also severe. The results provide further insight into the viability of conventional evacuation lifeboat systems in ice-covered water conditions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".