Overview of one year acoustical oceanography measurements on Chukchi shelf during Shallow Water Canada Basin Acoustic Propagation Experiment 2016–2017
Bibliographic record
Abstract
A multi-institutional, acoustical oceanography experiment was conducted from October 2016 through November 2017 on the Chukchi continental shelf covering 100–700 m isobaths. Parallel to a deep-water experiment conducted during the same period, the Shallow Water Canada Basin Acoustic Propagation Experiment (SW CANAPE) was designed to assess basin scale acoustic signals on the shelf region while detailed oceanographic dynamic of the shelf break region, particularly the upwelling and other dynamic of the upper 500 m water column, was measured simultaneously. Multiple arrays of oceanographic sensors including upward looking ice profiler, current profiler, temperature, conductivity, and pressure profiles measured temporal and spatial dynamics of 500 m upper ocean in connection with acoustic measurements. Distributed in a 30 km2 area north of Barrow Alaska, vertical line arrays including an L-shaped array, covered upper 200 m of the water column. Two acoustic sources placed at 148 m and 193 m depths on the shelf emitted broadband acoustic signals in frequency bands (700–1100 Hz, and 1400–4000 Hz) along and across the shelf while the sound speed and current profile and surface ice were being measured continuously. Deep water low frequency signals were also recorded. This talk provides an overview of the SW CANAPE experiment and highlights some of the detailed measurements. [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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".