Role of chemical and physical variables in regulating microcystin-LR concentration in phytoplankton of eutrophic lakes
Bibliographic record
Abstract
A survey of eutrophic to hypereutrophic hardwater lakes in central Alberta was conducted to test the hypotheses that the concentration of the cyanobacterial toxin microcystin-LR (MC-LR) in phytoplankton is regulated by environmental factors that affect both the biomass of the main producer of the toxin, Microcystis aeruginosa, and the concentration of the toxin in the cells. Of all environmental factors examined, total phosphorus was the strongest correlate of both M. aeruginosa biomass and cellular MC-LR (expressed as micrograms per gram of M. aeruginosa). Microcystis aeruginosa biomass was also strongly negatively related to the total nitrogen to total phosphorus ratio (TN:TP) and inorganic nitrogen (NO2-+ NO3-, NH4+). A univariate regression model of TN:TP explained the most variation in MC-LR concentration (expressed as nanograms of cellular toxin per litre) in mixed phytoplankton communities. This study indicated that MC-LR dynamics in phytoplankton of lakes was related to changes in the concentration and ratio of phosphorus and nitrogen.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".