What Drives the Mean Along‐Shelf Flow in the Northwest Atlantic Coastal Ocean?
Bibliographic record
Abstract
Abstract A long‐standing hypothesis is that the steady along‐shelf circulation in the Northwest Atlantic (NWA) coastal ocean is driven by buoyancy input from continental freshwater runoff. However, the forcing from the freshwater runoff has not been adequately evaluated and compared with other potential driving mechanisms. This study investigates the roles of both wind stress and freshwater runoff in driving the mean along‐shelf flow in the NWA coastal ocean and examines other potential drivers using a newly developed high‐resolution regional model with realistic forcing conditions. The results reveal that wind stress has a larger impact than freshwater runoff on the overall mean circulation and along‐shelf sea‐level gradient on the NWA shelf. While the continental freshwater input consistently contributes to the equatorward along‐shelf flow and higher sea level along the coast, wind stress is more effective for the setup of the broad‐scale circulation pattern by driving the along‐shelf flow on the Labrador Shelf and opposing the flow in the Mid‐Atlantic Bight and on the Scotian Shelf. In addition to the local wind and continental runoff, the sub‐Arctic inflow from higher latitude is an essential part of the NWA shelf circulation system. This remote driver directly contributes to the along‐shelf flow and insulates the shelf flow from the Gulf Stream on the southern shelves.
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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 | 0.000 |
| 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) | 0.001 | 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".