Acoustic recordings and modeling under seasonally varying sea ice
Bibliographic record
Abstract
Acoustic data from the Canada Basin Acoustic Propagation Experiment are discussed. These recordings were obtained under seasonally varying sea ice to the north of Alaska during a period of 154 days. They contain signals from sources that were deployed at ranges of 17.5, 29.6, and 237.8 km and ambient sounds from marine mammals and ice-related events. After the area was covered with ice, the amplitude of receptions from the most distant source gradually decreased as scattering features on the underside of the ice developed during fracturing, drifting, ridging, and rafting events. Improvements are presented for an Arctic acoustic model that is based on the parabolic equation method, and the approach is applied to a problem in which variable ice thickness acts as a loss mechanism by scattering energy out of the waveguide. Some of the recordings have a harmonic signature that is believed to be associated with the resonances of ice floes rubbing together, but variations in the harmonics over short time scales cannot be explained in terms of the resonances of an isolated floe. This behavior may be related to the coupling of vibrations at contact points that vary during the relative motions of floes.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".