A global perspective of entomopathogens as microbial biocontrol agents of insect pests
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growing global population has created a significant demand for both quality and quantity of agricultural products, resulting in a significant increase in the use of agrochemicals such as chemical pesticides to counter insect pests. Consumers, on the other hand, have grown increasingly concerned in recent years about the adverse effects of chemical insecticides on human health and the environment. As a result, researchers worldwide have been compelled to conduct research into alternative crop protection solutions. Biological control through entomopathogens has gained prominence among these alternatives, and several microbial biocontrol agents, including baculoviruses, Bacillus, Beauveria, Steinernema, and Heterorhabditis species, have been tested. Microbial biopesticide products are currently being used to combat specific insects that harm crops. The modes of action of entomopathogens, their advantages and constraints are discussed. An overview of processes for their development are highlighted with examples, as well as the issues that impede their development. Finally, special attention was paid to the gaps identified in this sector and the factors limiting their application particularly with respect to market potential. The future potential of entomopathogens may be affected by changing agricultural systems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it