Predicting Internal Solitary Waves in the Gulf of Maine
Bibliographic record
Abstract
Abstract Internal solitary waves (ISWs) are important physical processes in the Gulf of Maine (GoM), which is one of the most productive ecosystems of the Northwest Atlantic. In order to understand the roles that ISWs play, it is necessary to have synthesized knowledge of their timing and distributions. We detail the ISW spatial distribution patterns in the GoM using modern high‐resolution satellite imagery. A prediction methodology is suggested based on the speed of mode‐1 ISWs, which is cross validated using three methods: Remote sensing based on positional displacements of ISWs strips in continuous images, theoretical analysis based on climatological ocean stratification, and an empirical method based on bathymetry. Prediction accuracy is further validated by independently collected high spatial resolution satellite images from multiple sensors. We found a new‐generation site for ISWs near Grand Manan, with wave crests extending over the entire GoM. Interference of ISWs originating from the new‐generation site and the well‐known generation location on Georges Bank, plus local‐scale ISW generation sites, creates cross‐sea conditions within the water column, resulting in complex ISWs. We find that the background barotropic currents do not significantly influence the ISW spatial distributions, which simplifies the prediction of ISWs; we also consider the influence of tidal currents, general circulation, and stratification. This methodology is potentially useful for additional studies, for example, linking ISWs, energy and nutrient budgets, mixing, and primary production in the Gulf of Maine.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".