Spatial variations of CO <sub>2</sub> fluxes in the Saguenay Fjord (Québec, Canada) and results of a water mixing model
Bibliographic record
Abstract
Abstract. The Saguenay Fjord is a major tributary of the St. Lawrence Estuary and is strongly stratified. A 6–8 m wedge of brackish water typically overlies up to 270 m of seawater. Relative to the St. Lawrence River, the surface waters of the Saguenay Fjord are less alkaline and host higher dissolved organic carbon (DOC) concentrations. In view of the latter, surface waters of the fjord are expected to be a net source of CO2 to the atmosphere, as they partly originate from the flushing of organic-rich soil porewaters. Nonetheless, the intrusion, at the surface, of brackish water from the upper estuary with the rising tide, as well as mixing of seawater, overflowing the sill from the lower estuary, modulate the CO2 dynamics in the fjord. Using geochemical and isotopic tracers, in combination with an optimization multiparameter algorithm (OMP), we determined the relative contribution of known source-waters to the water column in the Saguenay Fjord, including waters that originate from the Lower St. Lawrence Estuary and replenish the fjord’s deep basins. These results, when combined to a conservative mixing model and compared to field measurements, serve to identify the dominant factors, other than physical mixing, such as biological activity (photosynthesis, respiration) and gas exchange at the air-water interface, that impact the water properties (e.g., pH, pCO2) of the fjord. Results indicate that the fjord’s surface waters are a net source of CO2 to the atmosphere during periods of high freshwater discharge (e.g., spring freshet) whereas they serve as a net sink of atmospheric CO2 when their practical salinity exceeds ~ 5–10.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".