Analysis of the relationship between level ice draft, ridge frequency and ridge keel draft for use in the probabilistic assessment of ice ridge loads on offshore structures
Why this work is in the frame
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Bibliographic record
Abstract
Level ice draft, ice ridge keel draft and ridge frequency are important variables in the probabilistic assessment of ice ridge loads on offshore structures. We use ice profiling sonar (IPS) measurements of ice draft from the Beaufort Sea to analyse the relationship between these three variables. We propose a probabilistic simulation technique of ridge keel drafts. Two examples of simulations are given. The first example simulates the weekly deepest ridges. The simulated distribution of the weekly deepest ridge keel draft agrees with the measured data. The second example simulates all ridges deeper than 5 m. This simulation results in overestimation of the ridge keel draft in the tail section of the distribution. For both simulations, with the relationships established in this paper, the only needed input is level ice draft. Future studies should investigate whether the relationships found in the Beaufort Sea are valid in other areas or if there is a possibility of scaling the correlations. If the correlations prove predictably scalable for other locations, it could be possible to estimate the ridge keel draft distribution and ridge frequency by knowing only the level ice draft (thickness) statistics. This study is our first endeavour in this direction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it