Quantifying wave measurement differences in historical and present wave buoy systems
Bibliographic record
Abstract
Abstract An intra-measurement evaluation was undertaken, deploying a NOMAD buoy equipped with three National Data Buoy Center and two Environment and Climate Change Canada-AXYS sensor/payload packages off Monterey, California; a Datawell Directional Waverider buoy was deployed within 19 km of the NOMAD site. The six independent wave measurement systems reported hourly estimates of the frequency spectra, and when applicable, the four Fourier directional components. The integral wave parameters showed general agreement among the five sensors compared to the neighboring Datawell Directional Waverider, with the Inclinometer and the Watchman performing similarly to the more sophisticated 3DMG, HIPPY, and Triaxys sensor packages. As the H m0 increased, all but the Inclinometer were biased low; however, even the Watchman reported reasonable wave measurements up to about 6–7 m, after which the H m0 becomes negatively biased up to about a meter, comparable to previous studies. The parabolic fit peak spectral wave period, T pp , results showed a large scatter, resulting from the complex nature of multiple swell wave systems compounded by local wind-sea development, exacerbated by a variable that can be considered as temporally unstable. The three directional sensors demonstrated that NOMAD buoys are capable of measuring directional wave properties along the western US coast, with biases of about 6 to 9 deg, and rms errors of approximately 30 deg. Frequency spectral evaluations found similarities in the shape, but a significant under estimation in the high frequency range. The results from slope analyses also revealed a positive bias in the rear face of the spectra, and a lack of invariance in frequency as suggested by theory.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".