Identifying metabolic indicators of phytoplankton and comparing the temporal changes in algal community composition in two Lake Ontario areas of concern
Bibliographic record
Abstract
Freshwater algal blooms transition into harmful algal blooms (HABs) when cyanobacteria produce toxins that impact ecosystem health. The point at which algal blooms transition into HABs is not fully understood, but I believe that the transition can be predicted by combining molecular and community-level information. This study consisted of ten weeks of sampling in 2020 from August to October in Hamilton Harbour and the Bay of Quinte, two Lake Ontario areas of concern (AOCs). Phytoplankton genus composition was obtained via microscopy and water quality was assessed. Metabolomics were performed using liquid chromatography tandem mass spectroscopy (LC-MS/MS) to identify changes in metabolites over time. The results from this study identified taurine, serine, and glycine in large amounts in both locations and that phytoplankton community composition is primarily affected by nitrates, total phosphorus, and turbidity. These findings will improve our understanding of these AOCs as well as the behaviour of phytoplankton overall.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".