Biodegradation of Chlorpyrifos by Microbes: A Review
Bibliographic record
Abstract
Chlorpyrifos (CP) is a widely used organophosphate pesticide known for its recalcitrant nature, raising concerns about potential ecological and health impacts due to its toxicity. Many plants and animals are contaminated with this pesticide. Microbial biodegradation offers an environmentally friendly and effective method to remove CP from the environment and mitigate its impacts, especially given its low cost, particularly when bioremediation is conducted on-site. Different types of microbial species have been found to function under various environmental conditions, with some, like Pseudomonas nitroreducens PS-2 and Pseudomonas aeruginosa (NCIM 2074), showing promising results with degradation rates of up to 100%. However, challenges exist, such as partial degradation caused by the presence of metabolites, and the recalcitrant nature of CP, which can impede microbes' ability to effectively degrade its hydrocarbon ring. Overall, a combination of approaches, such as microbial and algal methods, or the discovery of new microbial strains, can help overcome these challenges and further enhance the long-term viability of this technique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".