Sound propagation from the Canadian Basin to the Chukchi shelf during Summer 2015
Bibliographic record
Abstract
During the summer of 2015 a pilot experiment for the Canadian Basin Acoustic Propagation Experiment (CANAPE) was conducted between deep Arctic basin and shallow Chukchi shelf. A vertical line array (VLA) was deployed on the shelf (72.336 N, 157.449 W) at a depth of 161 m from July 26 to August 13, 2015. Sound sources were deployed from R/V Sikuliaq at locations ranging from 131 to 375 km from the VLA. M-Sequences centered at 250 Hz (bandwidth of 62.5 Hz) were transmitted from each location. Discrete shipboard CTD data were conducted at each transmission location and continuous CTD data were recorded along the VLA. Water column data suggests a sound channel located vertically between Pacific and Atlantic waters near the depth of Arctic halocline layer. They also show upward shoaling of lower halocline waters onto the shelf. This upwelling over the continental slope moves the sound channel from offshore to onshore near the bottom. The axis of this sound duct is 100 m below the surface and is about 100 m thick. Received acoustic signals on the shelf increase rapidly in intensity at time scales that range from minutes to days. In this paper we show the acoustic variations are due to the variable sound speed profile. Signal intensity, noise, and temporal variability for geotime scale of minutes to hours are reported. Numerical simulations are conducted to investigate the associated acoustic effects in data. [Work supported by ONR 322OA.]
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".