A revised seawater sound-speed equation consistent with deep acoustic travel times in the Beaufort Gyre
Bibliographic record
Abstract
Travel-time measurements from an ocean acoustic tomography array deployed in the central Beaufort Gyre during 2016–2017 for the Canada Basin Acoustic Propagation Experiment (CANAPE) have been previously used to test the accuracy of the internationally accepted sound-speed equation (TEOS-10) [Vazquez et al. (2023), J. Acoust. Soc. Am. 154, 2676–2688] concluding that TEOS-10 gives sound speeds at high pressure (>1000 m) and low temperature (<0°C) that are too high by 0.14–0.16 m s−1. Here, a revised seawater sound-speed equation is developed that is consistent with the CANAPE travel times. First, a revised seawater sound speed equation is formulated using maximum a posteriori estimates based on laboratory data, defining the priors of the system in a reproducible manner. This equation is subsequently updated by fitting to the CANAPE travel times through iterative least-squares. CTD casts conducted in the Arctic are employed to assess the discrepancies between the revised sound-speed equation and other sound-speed equations. While including the deep acoustic transmissions corrects the portion below 1000 m depth, it also slightly corrects an additional anomaly between 100 and 300-m that corresponds to temperatures as low as −1.8°C.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".