How islands cause phytoplankton to bloom in their wakes
Bibliographic record
Abstract
The development of phytoplankton blooms in Von Kàrmàn vortex streets in island wakes has been investigated using a coupled bio‐physical model which evolves a geostrophically balanced flow past a relatively small (L = 10 km) oceanic island. Three major processes associated with the “island mass effect” are found to occur in series in our numerical experiment. First, increases in phytoplankton were observed in the lee due solely to passive advection from the deep maximum. Second, following the shedding of cyclonic eddies, upwelled nitrate enhances local primary production in the surface euphotic layer resulting in a phytoplankton bloom. The bloom peaks appeared about two weeks downstream from the island. Third, a weaker bloom is also found in the immediate lee of the island, associated with nutrient injection and longer residence time of upwelled water. The demonstrated detailed features of island mass effect are remarkably consonant with previously observed phenomena in the real ocean.
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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 | 0.000 | 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".