Exposure to ultraviolet radiation in aquatic ecosystems: estimates of mixing rate in Lake Ontario and the St. Lawrence River
Bibliographic record
Abstract
Vertical eddy diffusion coefficients (Kz) were determined for the surface waters at several sites in Lake Ontario and along the Upper St. Lawrence River using the water column distribution patterns of hydrogen peroxide. Values of Kzranged from 0.45 × 10-3to 23 × 10-3m2·s-1in Lake Ontario and from 0.75 × 10-3to 2.1 × 10-3m2·s-1along the St. Lawrence River. The residence time for bacterioplankton and phytoplankton in the surface waters was then determined from the Kzvalues and incorporated into a spectral model to determine the continuous biologically effective exposure to ultraviolet radiation (E*UVR). The values of E*UVRfor stations where the temperature fine structure profiles indicated near-surface warming (diurnal thermocline formation) were higher (149.1 J·m-2) than at stations with isothermal surface waters (3.0 J·m-2). Model calculations for two contrasting bays of a lake underscored the dominant role of diurnal thermocline formation in increasing the duration of exposure to continuous damaging ultraviolet radiation exposure. The E*UVRvalue for the near-surface bacterioplankton in a humic stained bay was higher (219.2 J·m-2) than in a larger bay with lower concentrations of chromophoric dissolved organic matter (47.83 J·m-2).
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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 | 0.001 |
| 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".