Effect of spirotetramat and 2,4-dichlorophenoxyacetic pesticides on two phytoplankton species ( <i>Monoraphidium griffithii</i> and <i>Coscinodiscus</i> sp.) in a single and compound mixture laboratory exposure
Bibliographic record
Abstract
This study was carried out to assess the chronic effects of both an insecticide (spirotetramat) and a herbicide (2,4-Dichlorophenoxyacetic acid) on two phytoplankton species: Monoraphidium griffithii and Coscinodiscus sp. The effects of the chemicals on an exponentially-growing population of the two species were evaluated using single compounds and a compound mixture. The experiments lasted for 27 days. The results show a decrease in the populations’ growth for both species after the application of single pesticides and the mixture. 2,4-D applied alone and the mixture of both chemicals have affected the organisms the most. Both pesticides have induced an increase in chlorophyll-a content in M. griffithii while no effect was observed on chlorophyll-a in Coscinodiscus sp. A significant effect was recorded in the cell size of both species with both pesticides. The two spirotetramat tested concentrations have induced an increase in cell size, while the opposite effect was obtained for the (2,4-D) herbicide concentrations. The mixture of compounds induced an additive effect on the cell size of both species. These results indicate the risk which the two chemicals represent in a natural environment. They are agents that can have chronic impairments at the physiology or behavior level of such phytoplankton species as M. griffithii or Coscinodiscus sp. Such impairments might consequently affect the health of the ecosystem.
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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 | 0.000 | 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".