Studies of Internal Waves in the Strait of Georgia Based on Remote Sensing Images
Bibliographic record
Abstract
This paper analyzes over 500 sets of internal waves in the Strait of Georgia (British Columbia, Canada) based on a large number of satellite remote sensing images. The spatial and temporal distribution of internal waves in the central region of the strait are discussed via statistical analysis. Possible generation origins of the observed internal waves are divided into three categories based on their different propagation directions and geographical locations: (1) the interaction between the narrow channels to the south of the Strait and the tidal currents, leading to the formation of mainly eastward and northward propagating waves; (2) the interaction between the tidal currents and the topography near Point Roberts, resulting in mainly westward propagating waves; (3) excitation by river plume, mainly near Fraser River mouth, leading to the formation of mainly westward waves along the direction of the river plume. The relation between the occurrence of internal waves in remote sensing images and wind or tide level is also discussed. It is found that most of the observed internal waves occur at low tides. However, due to the influence of the river, the eastward propagating internal waves near the river mouth seldom occur at the lowest tide. Also, internal waves are captured more easily by remote sensing images in summer due to the lower wind speed than winter and therefore the seasonal distribution of internal waves in remote sensing images may not be able to completely represent the real situation in the study area. Finally, combining the in situ measured data and model output data, the Benjamin-Ono equation is found to satisfyingly simulate the characteristic parameters of the studied internal waves.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".