Molecular Characterization of Potential Microcystin-Producing
Bibliographic record
Abstract
The distribution and genotypic variation of potential microcystin (MC) producers along the southern and eastern shores of Lake Ontario in 2001 and 2003 were examined using a suite of PCR primers. Cyanobacterial, Microcystis sp., and Microcystis-specific toxin primer sets identified shoreline distribution of cyanobacterial DNA (in 97 % of the stations) and MC synthetase genes (in 50 % of the stations). Sequence analysis of a partial mcyA amplicon targeting Microcystis, Anabaena, and Planktothrix species indicated that the Microcystis sp. genotype was the dominant MC genotype present and revealed a novel Microcystis-like sequence containing a 6-bp insert. Analysis of the same samples with genus-specific mcyE primers confirmed that the Microcystis sp. genotype was the dominant potential MC producer. Genotype compositions within embayments were relatively homogenous compared to those for shoreline and tributary samples. MC concentrations along the shoreline exhibited both temporal and spatial differences as evidenced by the protein phosphatase inhibition assay, at times exceeding the World Health Organization guideline value for drinking water of 1.0 g MC-LReq liter 1. MC genotypes are widespread along the New York State shoreline of Lake Ontario, appear to originate nearshore, and can be carried through the lake via wind and surface water current patterns. Lake Ontario is the easternmost and smallest of the Great
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".