Bibliographic record
Abstract
Abstract. The Atlantic Zone Monitoring Program (AZMP) was established by Fisheries and Oceans Canada (DFO) in 1998 with the aim of monitoring physical and biological ocean conditions in Atlantic Canada in support of fisheries management. Since 2014, at least two of the carbonate parameters (pH, Total Alkalinity - TA, Dissolved Inorganic Carbon - DIC) have also been systematically measured as part of the AZMP, enabling the calculation of derived parameters (e.g., carbonate saturation states - Ω, partial pressure of CO2 - pCO2, etc.). The present study gives an overview of the spatiotemporal variability of these parameters between 2014 and 2020. Results show that the variability of carbonate parameters reflects changes in both physical (e.g., temperature, salinity) and biological (e.g., plankton photosynthesis and respiration) parameters. For example, most of the region undergoes a seasonal warming and freshening. While the former will tend to increase Ω, the latter will decrease both TA and Ω. Spring and summer plankton blooms decrease DIC near the surface and then remineralize and increase DIC at depth in the fall. The lowest pCO2 values are located in the cold Coastal Labrador Current and the highest in the fresh waters of the Gulf of St. Lawrence and the St. Lawrence Estuary. The latter is also the host of the lowest pH values of the zone. Finally, most of the bottom waters of the Gulf of St. Lawrence are undersaturated with respect to aragonite (Ωarg<1). In addition to providing a baseline of carbonate parameters of the Atlantic Zone as a whole, this comprehensive overview is a necessary and useful contribution for the modeling community and for more in-depth studies. The full data set of measured and derived parameters is available in the Federated Research Data Repository at https://doi.org/10.20383/102.0673.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.027 | 0.025 |
| Insufficient payload (model declined to judge) | 0.164 | 0.144 |
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".