The Sensitivity of Ice Keel Statistics to Upward Looking Sonar Ice Draft Processing Methods
Bibliographic record
Abstract
Abstract Upward looking sonar (ULS) instruments have been used for several decades to provide continuous measurements of ice draft. The time resolution of the ice draft observations is typically 1–2 seconds. When fused with ice drift speed observations, a high horizontal spatial resolution can be realized. Such a high resolution allows for the identification of individual ice keel features and an analysis of their spatial characteristics. Many methods are available for transforming the ice draft series from an equispaced time domain to an equidistant spatial domain. This paper analyzed the sensitivity of ice keel statistics to three transformation methods applied to ULS sea ice measurements in the Beaufort Sea and North Chukchi Sea. Although differences were found between the methods, these were related to episodes when the sampling frequency is not high enough to profile an ice draft feature travelling with a high drift speed. Knowledge of maximum drift speeds in the region of a measurement location along with the enhanced power and storage capacities of modern ice profilers enable sampling configurations which avoid this scenario.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".