Modeling the influence of North Atlantic freshening on phytoplankton dynamics in the Nova Scotian Shelf and Gulf of Maine region
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.A coastal oceanographic-meteorological instrumentation network in the Basque Country (six coastal stations, combining atmospheric and oceanographic sensors) has been implemented recently, with two offshore buoys (Wavescan); these are moored off Cape Matxitxako and San Sebastián, at 550 m and 630 m water depth, respectively. These buoys provide real-time data of meteorological variables (air temperature, atmospheric pressure, vectorial wind, solar and net radiation) and oceanographic parameters (directional waves, current profile in the upper 200 m of the water column, and eight temperature and salinity measurement points from the surface down to 200 m water depth). Both the coastal stations and offshore buoys belong to the Department of Transport and Civil Works of the Basque Government. The network of sensors provides high-frequency, coupled data sets of oceanographic and meteorological variables. Enlargement of the network, in terms of distance offshore and width of the water column covered, will provide new data for input and hindcasting calibration of hydrodynamic and dispersion models. An IBM (Individual Based Model), coupled to ROMS hydrodynamic model (Regional Ocean Modelling System), is used in the Basque Coast for descriptive and forecasting purposes on the transport of oil spills, sediments, fish eggs and larvae, etc. Moreover, high-frequency temperature and salinity profiles, together with the atmospheric and dynamical variables, permit the high-resolution tracking of shelf and slope processes, such as thermocline fluctuations related to wind fields, Ekman transport, and the expansion of river plumes. Examples of applications and results are presented in this contribution.
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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 | 0.000 | 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".