Bibliographic record
Abstract
In this paper, one of the widely-used ice resistance prediction methods, introduced by Spencer(1992) of the Institute for Ocean Technology, Canada, is reviewed. Spencer's component-based scaling system for ship-ice model tests is analysed to estimate the ice resistance of various types of icebreaking vessels (Canadian MV Arctic, Terry Fox, R-Class icebreaker, US icebreakers Polar Star and Healy, Russian SA-15 cargo ships, Japanese PM Teshio and a model ship). The general form and the non-dimensional coefficients in ice resistance prediction formula are obtained using the published ice model test and full-scale sea trial data. The applicability of Spencer's method on R-Class icebreaker is discussed to estimate ice resistance for the larger icebreaking cargo vessels. Additional parameters to account for the difference in hull forms of icebreakers and cargo vessels are recommended to be included in the Spencer's original ice resistance prediction formula.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".