Travel-time variability during the 2016–2017 deep-water Canada Basin Acoustic Propagation Experiment
Bibliographic record
Abstract
The Arctic Ocean is undergoing dramatic changes in response to increasing atmospheric concentrations of greenhouse gases. The decreases in ice extent, the near disappearance of multiyear ice, and changes in the stratification of the ocean all have important implications for underwater acoustic propagation. During the 2016–2017 Canada Basin Acoustic Propagation Experiment (CANAPE), a long vertical receiving array was embedded within an ocean acoustic tomography array of six acoustic transceivers with a radius of 150 km. The impulse response of the ocean was measured every four hours using broadband signals centered at about 250 Hz. The observed travel-time variability was extraordinarily low, reflecting both the low internal-wave energy level and sparseness of mesoscale eddies in the Canada Basin. The peak-to-peak travel time variability of the early, resolved ray arrivals was only a few tens of milliseconds, and the standard deviations over the entire year were only a few milliseconds. The travel-time spectra show increasing energy at lower frequencies and enhanced semidiurnal variability, presumably due to some combination of the semidiurnal tides and inertial variability. The travel-time fluctuations are roughly an order of magnitude smaller than is typical in midlatitudes at similar ranges.
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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".