Coastal Ocean Physics and Red Tides: An Example from Monterey Bay, California
Bibliographic record
Abstract
Dense accumulations of certain phytoplankton make the ocean appear reddish.Some of these "red tides" poison marine life and negatively impact coastal fi sheries and human health.Complex variability in coastal waters coupled with rudimentary understanding of phytoplankton ecology challenge our ability to understand and predict red tides.During fall 2002, multi-scale physical and biological observations were made preceding and during a red tide bloom in Monterey Bay, California.These intensive observations provided insight into the physical oceanography underlying the event.The bloom was preceded by intrusion of a warm, chlorophyllpoor fi lament of the California Current, suddenly changing physical and biological conditions through most of the bay.Enhancement of vertical density stratifi cation followed the intrusion and created conditions favoring dinofl agellates.Favorable environmental conditions led to red tide inception in the northern bay, and advection strongly infl uenced spread of the bloom throughout the bay and out into the adjacent sea.Concentration of dinofl agellates in convergence zones was indicated by the development of dense red tide patches in fronts and in wavelike aggregations having the same scale as internal waves that propagated through the bloom.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".