Spatial variability of surface-water pCO <sub>2</sub> and gas exchange in theworld's largest semi-enclosed estuarine system: St. Lawrence Estuary(Canada)
Bibliographic record
Abstract
Abstract. The incomplete spatial coverage of partial pressure of CO2 (pCO2 ) measurements across estuary types represents a significant knowledge gap in current regional- and global-scale estimates of estuarine CO2 emissions. The Estuary and Gulf of St. Lawrence (EGSL) at the lower limit of the subarctic region in eastern Canada is the largest estuarine system in the world, and is characterized by an exceptional richness in environmental diversity. It is among the world's most intensively studied estuaries, yet there are no published data on its surface-water pCO2 distribution. To fill this data gap, a comprehensive dataset was compiled from direct and indirect measurements of carbonate system parameters in the surface waters of the EGSL during the spring or summer of 2003–2016. The calculated pCO2 ranged from 435–765 μatm in the shallow, partially mixed Upper Estuary, 139–578 μatm in the deep, stratified Lower Estuary, and 207–478 μatm along the Laurentian Channel in the Gulf. Overall, at the time of sampling, the St. Lawrence Estuary served as a weak source of CO2 to the atmosphere, with an area-averaged CO2 degassing flux of 1.00 to 2.06 mmol C m−2 d−1 (0.37 to 0.75 mol C m−2 yr−1). A preliminary analysis of factors controlling the spatial variability of surface-water pCO2 reveals that respiration (Upper Estuary), photosynthesis (Lower Estuary), and temperature (Gulf) are dominant controls.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".