Transmission loss of surface-reflected ray arrivals underneath seasonally varying sea ice in the Canada Basin during 2016–2017
Bibliographic record
Abstract
During the 2016-2017 Canada Basin Acoustic Propagation Experiment, an ocean acoustic tomography array with a radius of 150 km measured the impulse responses of the ocean every 4 hr at a variety of ranges and bearings using broadband signals with center frequencies from 172.5 to 275 Hz. Ice-profiling sonar data showed a gradual increase in ice draft over the winter with daily median ice drafts reaching maxima of about 1.5 m and daily standard deviations reaching maxima of about 1.2 m. The travel-time variability of early, resolved arrivals from refracted-surface-reflected rays with lower turning depths below 500 m was reported in a previous paper [Worcester et al. (2023). J. Acoust. Soc. Am. 153, 2621-2636]. Here, the transmission loss of these same ray arrivals is analyzed. The transmission loss was lowest when open water was present and increased as the ice draft increased. The excess transmission loss per surface reflection, defined as the increase in transmission loss relative to open water conditions, increased with center frequency and surface grazing angle. The combination of transmission loss measurements for resolved ray arrivals and ice drafts from the ice-profiling sonars provides an excellent dataset for testing ice-scattering models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".