Bibliographic record
Abstract
Biological control provides a sustainable and environmentally friendly alternative to chemical methods for managing agricultural pests. Wheat, as a major global crop, faces significant threats from pest infestations and requires effective management strategies. This study conducted a meta-analysis to evaluate the effectiveness, sustainability, and influencing factors of biological control strategies for wheat pests. The role of key control factors such as parasitic wasps, predatory insects, entomopathogenic fungi, and bacteria in suppressing pest populations was analyzed, emphasizing the advantages of biological control over chemical methods, especially in terms of long-term sustainability and ecological benefits. It was found that climate conditions, crop management practices, and interactions with local biodiversity have a significant impact on the success of biological control work. Case studies from specific wheat planting areas demonstrated the practical application and challenges of implementing biological strategies, introduced new biological control agents, integrated with precision agriculture, and the potential for policy interventions to improve the effectiveness of biological control in wheat pest management. The sentence is:. This study aims to emphasize the importance of promoting biological control as the cornerstone of sustainable agriculture.
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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.056 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".