Ocean acoustic tomography in the Beaufort Gyre
Bibliographic record
Abstract
An ocean acoustic tomography array with a radius of 150 km was installed in the central Beaufort Gyre during 2016–2017 for the Canada Basin Acoustic Propagation Experiment (CANAPE). Five transceivers were deployed in a pentagon shape with a sixth transceiver at the center and a long vertical receiving array northwest of the central mooring. At least 12 refracted-surface-reflected (RSR) ray arrivals with lower turning points at depths between 500 and 3500 m were resolved in the acoustic receptions at all receivers. Travel-time anomalies were computed relative to a range-dependent sound-speed reference made by objectively interpolating annual-average sound-speed profiles constructed from the temperature data at each mooring. The travel time anomalies were inverted to estimate the 3-D sound-speed anomaly, including corrections to the positions of sources and receivers consistent with the uncertainty from long-baseline acoustic navigation systems at each mooring. Although the deep water in the Canada Basin is nearly homogeneous in temperature and salinity and highly stable (slowly warming in response to geothermal heating), it proved necessary to allow for a sound-speed change in the deep ocean to obtain consistent inversions, suggesting that the sound-speed equation at high pressure and low temperature is in error by about 0.1–0.2 ms−1.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".