Modeling ocean circulation and biogeochemical variability in the Gulf of Mexico
Bibliographic record
Abstract
Abstract. A three-dimensional coupled physical-biogeochemical model is applied to simulate and examine temporal and spatial variability of circulation and biogeochemical cycling in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data assimilative global ocean circulation model, and observed freshwater and terrestrial nitrogen input from major rivers. A 7 yr model hindcast (2004–2010) was performed, and validated against satellite observed sea surface height, surface chlorophyll, and in situ observations including coastal sea level, ocean temperature, salinity, and dissolved inorganic nitrogen (DIN) concentration. The model hindcast revealed clear seasonality in DIN, phytoplankton and zooplankton distributions in the GoM. An empirical orthogonal function analysis indicated a phase-locked pattern among DIN, phytoplankton and zooplankton concentrations. The GoM shelf nitrogen budget was also quantified, revealing that on an annual basis the DIN input is largely balanced by the removal through denitrification (an equivalent of ~ 80% of DIN input) and offshore exports to the deep ocean (an equivalent of ~ 17% of DIN input).
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".