Seasonal and interannual variability of physical and biological dynamics at the shelfbreak front of the Middle Atlantic Bight: nutrient supply mechanisms
Bibliographic record
Abstract
Abstract. A high-resolution, 3-dimensional coupled biophysical model is used to simulate ocean circulation and ecosystem variations at the shelfbreak front of the Middle Atlantic Bight (MAB). Favorable comparisons between satellite observations and model hindcast solutions from January 2004 to November 2007 indicate the model has intrinsic skills in resolving fundamental physical and biological dynamics at the MAB shelfbreak. Seasonal and interannual variability of ocean physical and biological states and their driving mechanisms are further analyzed. The domain-wide upper water column nutrient content is found to peak in late winter-early spring. Phytoplankton spring bloom starts 1–2 months later, followed by zooplankton bloom in early summer. Our analysis shows the variability of shelfbreak nutrient supply is controlled by local mixing that deepens the mixed layer and injects deep ocean nutrients into the upper water column and alongshore nutrient transport by the shelfbreak jet and associated currents. Nutrient vertical advection associated with the shelfbreak bottom boundary layer convergence is another significant contributor. Spring mean nutrient budget diagnostics along the Nantucket transect are compared between nutrient rich 2004 and nutrient poor 2007. Physical advection and diffusion play the major role in determining strong interannual variations in shelfbreak nutrient content. The biological (source minus sink) term is very similar between these two years.
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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 | 0.000 |
| 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".