Modelling of the seasonal patterns of dimethylsulphide production and fate during 1989 at a site in the North Sea
Bibliographic record
Abstract
This modelling study aimed to extend our understanding of the biogeochemistry of the climatically active gas dimethylsulphide (DMS) in marine surface waters to an annual cycle. Processes involved in the production and fate of DMS and its precursor β-dimethylsulphoniopropionate (DMSP), a product of phytoplankton synthesis, were incorporated into a complex, coupled one-dimensional physical ecosystem model (European Regional Seas Ecosystem Model (ERSEM) and the General Ocean Turbulence Model (GOTM)) to create a model of DMS biogeochemistry at a seasonally stratified site in the North Sea for 1989. The model was validated against nutrient concentrations, biological standing stocks, biological production, DMS and DMSP concentrations, and DMS sea to air flux determined throughout 1989 during the North Sea Project. The validation results demonstrated that complex ecosystem models, combined with a comprehensive network of processes that control the production and fate of DMSP and DMS, could accurately mimic DMS biogeochemistry. The model provides insights into the impact of seasonally changing physical forcing on the relative contribution of individual processes to DMS production and sea to air flux.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".