Phytoplankton assemblages in the St. Lawrence River, downstream of its confluence with the Ottawa River, Quebec, Canada
Bibliographic record
Abstract
Consistent differences in physical, chemical, and biological characteristics were observed along a transversal river section located 2 km downstream of the confluence of the Ottawa and the St. Lawrence rivers. Phytoplankton sampled at stations subject to the influence of the St. Lawrence River had a lower biomass, smaller cell volume, lower chlorophyll a, and lower taxa richness than did phytoplankton at stations influenced by the Ottawa River. The stations influenced by St. Lawrence River waters showed regular seasonal changes in phytoplankton biomass and composition, reflecting the major impact of the stratification and mixing cycles observed in the Great Lakes. By comparison, at the stations influenced by Ottawa River waters, monthly variations were found in biomass and composition correlated with temperature and water clarity, suggesting the effects of the watershed's morphology. A discharge reduction of 12% in the St. Lawrence River and 46% in the Ottawa River between summer 1994 and summer 1995 coincided, for stations in both water masses, with lower biomass and greater species richness and an increase in taxa that generate noxious smells and odours. Phytoplankton is recommended for use in monitoring the biological impacts of changes in water characteristics resulting from human activities and climate change in the Great Lakes watershed.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".