Allelopathic effects of the toxic cyanobacteriumMicrocystis aeruginosa on duckweed,Lemna gibba L.
Bibliographic record
Abstract
Cyanotoxins are a group of compounds produced by cyanobacteria that can have severe physiological effects on other organisms, including humans. The potential allelopathic effects of Microcystis aeruginosa, a toxic cyanobacterium, on the duckweed plant, Lemna gibba L., were examined using three experimental methods: (1) a series of toxicity bioassays, (2) evaluation of toxin production by M. aeruginosa in the direct and indirect presence of L. gibba, and (3) inhibition of oxygen evolution in photosynthesis. The results showed that, first, there were no clear dose-dependent effects of the microcystin-LR standard or the toxic M. aeruginosa culture filtrate on any of the end points measured in the toxicity bioassays (plant and frond number, dry weight, growth rate, chlorophyll content; one-way ANOVA, p > 0.05). In those cases in which an EC(50) value could be obtained, chlorophyll a was the most sensitive end point, as it had the lowest EC(50) value (14.47 microg/L microcystin-LR) of all the end points. Second, the presence of L. gibba did not result in higher microcystin-LR production in the toxic M. aeruginosa culture. And, last, oxygen evolution was not affected in isolated chloroplasts exposed directly to microcystin-LR. Therefore, microcystins from the toxic cyanobacterium Microcystis aeruginosa do not appear to have an allelopathic effect on the common aquatic macrophyte Lemna gibba.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".