Subsea Risk Update Using High Resolution Iceberg Profiles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The current practice for protecting wellheads and associated subsea facilities from icebergs on the Grand Banks is an Excavated Drill Centre (EDC), which is simply an excavation in the seabed in which wellheads and associated facilities are placed. Free-floating icebergs simply drift over an EDC, with the exception of those that roll as they pass over an EDC and increase draft sufficiently to enter. The risk from gouging icebergs entering an EDC is a function of the clearance between the surrounding undisturbed seabed and the top of the facilities in the EDC, and the distribution of gouging iceberg keel penetration depths. A field program conducted in Bonavista Bay in 2015 was used to estimate iceberg rolling rates, and an analysis of high resolution iceberg profile data collected in 2012 was used to determine the associated distribution of iceberg draft changes that occur due to rolling, and thus the rate at which iceberg keels penetrate an EDC due to rolling events. Modeled iceberg grounding rates and iceberg scour data from the Jeanne d’Arc were used to estimate the rate at which gouging icebergs enter EDCs. Iceberg gouge data from the Jeanne d’Arc and a dynamic time-step iceberg simulation using the 2012 iceberg profile data were used to determine the impact rate for facilities in the EDC as a function of the distance between the midline and the top of the facilities (clearance). The analysis addresses some of the conservatisms in the current approach, allowing for reduced EDC excavation depths.
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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 | 0.000 | 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 | 0.000 | 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