The influence of bottom water intrusion events on the biogeochemistry of a coastal fjord
Bibliographic record
Abstract
Lack of bottom water exchange in fjord-like estuaries can result in low oxygen conditions and creating sites of redox-sensitive biogeochemical processes, such as denitrification. In many of these systems, occasional intrusions of well-oxygenated bottom water may temporarily alter redox gradients and sediment-water biogeochemistry. Quantifying the magnitude and importance of these changes is a challenge due to the short timescales over which these events can occur. Here we present results from Bedford Basin, a 71 m deep coastal fjord in eastern Canada, where a 20-year, weekly timeseries of bottom water conditions indicates that autumn wind-driven intrusion events are a common, but infrequent, feature of its circulation. To examine the impact of these intrusions on biogeochemistry, we deployed a benthic instrument pod at 60 m depth to record high-resolution measurements of temperature, salinity, nitrate, oxygen, and fluorescence over a 4-month period during the fall of 2018. During this time we captured two intrusion events, one in mid-Oct and another in mid-Nov. Both intrusion events occurred on a timescale of hours and resulted in sharp changes in temperature, salinity, oxygen, and nitrate. We used these measurements to constrain a coupled sediment-water column reactive transport model to examine the immediate and annual impacts of these intrusion events on oxygen and nitrogen dynamics in the basin bottom waters and across the sediment-water interface.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".