A new version of the SWIFT platform for waves, currents, and turbulence in the ocean surface layer
Bibliographic record
Abstract
The Surface Wave Instrument Float with Tracking (SWIFT) is a freely drifting platform for measurements of waves, currents, and turbulence in the ocean surface layer. This platform has been used globally to study wave breaking, wave-current interactions, and waves in ice. A new version (v4) of the buoy has recently been developed and demonstrated in the Office of Naval Research “Langmuir Circulations” field campaign along the California coast (2017). The new version is built around a 5-beam Acoustic Doppler Current Profiler (Nortek Signature 1000) with a multi-pulse coherent mode for high-resolution turbulence measurements. The new Doppler profiler enables estimates of the turbulent dissipation rate down to 3.5 m below waves, compared with 0.5 m in the previous version, and can measure a much larger range of turbulence levels than the previous version. The new version also uses a broadband Doppler mode to profile the mean currents down to 20 m. Mean Eulerian velocity profiles are estimated from the wave-averaged profiler velocities by applying a wave-following bias correction that scales with the Stokes drift and has twice the vertical decay scale. Finally, the new version supports real-time telemetry of raw sea surface elevations for reconstruction of individual waves by processing a coherent array of multiple SWIFTs, with applications for short-range wave-by-wave forecasting. These combined improvements to the platform are intended to advance understanding of wave processes and applications in the ocean surface layer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.019 |
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".