Role of Entomopathogenic Nematodes in Organic Farming and Sustainable Development
Bibliographic record
Abstract
Chemical fertilizers and pesticides are presently accumulating in the environment harming the ecosystem, causing pollution, and spreading some of the diseases. Nematodes can be considered as entomopath¬ogenic (EPN) if they fulfil criteria for entomo-pathogenicity when they bearing a pathogenic bacterium within a dauer juveniles juvenile, releasing the bacterium within the host, active host-seeking and penetration by dauer, rap¬id insect death, nematode and bacterial reproduction, reassociation of the pathogenic bacteria with new generations of dauer juveniles; and emergence of IJs from the cadaver so that the cycle can be repeated. Synthetic chemical pesticides have various disadvantages which include crop and soil contamination; killing of beneficial fauna and flora; resistance development in insects and adverse effects due to contamination in food chain and other environment related issues. To minimize pesticides contamination, EPN were identified as biological control agents and most suitable natural enemies of problematic insects because they reduce risk to humans and other related vertebrates
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".