Mapping of sea surface nutrients in the North Pacific: Basin-wide distribution and seasonal to interannual variability
Bibliographic record
Abstract
Monthly maps of sea surface nutrient (phosphate, nitrate, and silicate) concentrations were produced for the North Pacific (10°N–60°N, 120°E–90°W) for the years 2001–2010 using a selforganizing map trained with temperature, salinity, chlorophyll-a concentration, and mixed layer depth. Nutrient sampling was carried out mainly by ships of opportunity, providing good seasonal coverage of the surface ocean. Using the mapping results, we investigated the spatiotemporal variability of surface North Pacific nutrient and dissolved inorganic carbon (DIC) distributions on seasonal and interannual time scales. Nutrient and DIC concentrations were high in the subarctic in winter and low in the subtropics. In the summer, substantial amount of nutrients remained unutilized in subarctic and the northern part of the subarctic-subtropical boundary region while that was not the case in the southern part of the boundary region. In the subtropics, nutrients were almost entirely depleted throughout the year, while DIC concentrations showed a north-south gradient and significant seasonal change. Nutrients and DIC show a large seasonal drawdown in the western subarctic region, while the drawdown in the eastern subarctic region was weaker, especially for silica. The subarctic-subtropical boundary region also showed a large seasonal drawdown, which was most prominent for DIC and less obvious for nitrate and silicate. In the interannual time scale, the Pacific Decadal Oscillation was related to a seesaw pattern between the subarctic-subtropical boundary region and the Alaskan Gyre through the changes in horizontal advection, vertical mixing, and biological production.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".