Azimuthal dependence of the acoustic field in a year long Canada Basin Acoustic Propagation Experiment
Bibliographic record
Abstract
As in the mid-latitudes, the variability of the oceanography in the arctic ocean causes azimuthal dependent acoustic fields induced by the environmental parameters, such as the variable sound speed profile and bathymetry. Preliminary analysis of a year-long experimental data from “deep-to-shallow” and the “shallow-water” Canada Basin Acoustic Propagation Experiment (SW CANAPE) shows strong azimuthal variability of broadband signals recorded on 11 spatially distributed acoustic receiver arrays on the Chukchi shelf from September 2016 to October 2017. Particular attention is paid on geotimes pertaining to the variable sound speed profiles around the dynamic shelf-break region. Although acoustic modeling of the propagation requires a physics based ocean model for a complete modeling exercise, preliminary determination of the azimuthal behavior of broadband propagation is conducted using multiple two-dimensional Parabolic Equation (Nx2D) with the collected oceanographic data. Calculations for long-range, as well as short-range, source-receiver pairs in the SW CANAPE data show that azimuthal variabilities occur frequently and are related to the spatial and temporal characteristics of signal dispersion for different range and geotime scales. [Work supported by ONR.]
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".