Robust wavebuoys for the marginal ice zone: Experiences from a large persistent array in the Beaufort Sea
Bibliographic record
Abstract
An array of novel directional wavebuoys was designed and deployed into the Beaufort Sea ice cover in March 2014, as part of the Office of Naval Research Marginal Ice Zone experiment. The buoys were designed to drift with the ice throughout the year and monitor the expected breakup and retreat of the ice cover, forced by waves travelling into the ice from open water. Buoys were deployed from fast-and-light air-supported ice camps, based out of Sachs Harbour on Canada’s Banks Island, and drifted westwards with the sea ice over the course of spring, summer and autumn, as the ice melted, broke up and finally re-froze. The buoys transmitted heave, roll and pitch timeseries at 1 Hz sample frequency over the course of up to eight months, surviving both convergent ice dynamics and significant waves-in-ice events. Twelve of the 19 buoys survived until their batteries were finally exhausted during freeze-up in late October/November. Ice impact was found to have contaminated a significant proportion of the Kalman-filter-derived heave records, and these bad records were removed with reference to raw x/y/z accelerations. The quality of magnetometer-derived buoy headings at the very high magnetic field inclinations close to the magnetic pole was found to be generally acceptable, except in the case of four buoys which had probably suffered rough handling during transport to the ice. In general, these new buoys performed as expected, though vigilance as to the veracity of the output is required.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".