Clarification of cyanotoxins in El Guajaro Reservoir, Colombia using a microalgae‐based consortium MPMC
Bibliographic record
Abstract
Abstract BACKGROUND Cyanobacteria blooms occur in freshwater and saline ecosystems under certain environmental conditions, such as eutrophication, that are often accompanied by the production of cyanotoxins; Those biological toxins are a risk to the health of animals and humans. The eutrophication of water bodies is becoming more frequent due to organic pollution pressure from swage discharge, so outcrops are frequent and difficult to manage by the communities affected by these phenomena. Most of the control mechanisms for these events are carried out through nutrient input constraints, sonication, and (more recently) biological control. RESULTS In this work, a cyanobacterial bloom in a reservoir in a tropical zone of northern Colombia was characterized. The microbiological dominance of Microcystis sp. and the presence of microcystin in the water were documented. A bioaugmentation process was then tested with a microbial consortium containing a predominance of microalgae (MCPM); after this, the dominance of cyanobacteria was broken and the richness and density of the phytoplankton were recovered. The decrease in cyanobacterial density was documented 15 days after the MCPM bioaugmentation began. A significant removal (34% to 53%) of Microcystis sp, was observed between days 1 and 16; from day 16 to day 58, removal of Microcysis sp reached 92% to 100%. The bioaugmentation took a total of 58 days. CONCLUSION This work raises the possibility of using the competitive inhibition capacity of nonharmful microalgae on cyanobacteria as an ecological tool to counteract blooms and mitigate the risk of cyanotoxins for animals and humans. © 2021 Society of Chemical Industry (SCI).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".