Integral stochastic ordering of the multivariate normal mean-variance and the skew-normal scale-shape mixture models
Bibliographic record
Abstract
Metarhizium anisopliae (Metsch.) Sorokīn is an entomopathogenic fungus with broad bio insecticidal potential, widely recognized for its role in sustainable pest management. This review examines the taxonomy, pathogenesis, infection symptoms, environmental requirements, host specificity, and dual role as both a biocontrol agent and an endophyte. Special emphasis is placed on its efficacy against the cacao pod borer (Conopomorpha cramerella Snellen), a significant pest in Southeast Asia that causes yield losses exceeding 50% in cacao plantations. Laboratory and semi-field studies report larval mortality rates of up to 80%–90% under controlled conditions. However, field-level efficacy varies due to environmental factors such as temperature, relative humidity, UV exposure, and soil characteristics. The review also discusses formulation strategies, including conidial suspensions and granular formulations, that improve fungal persistence and infection success. Despite promising outcomes, the effectiveness of M. anisopliae is influenced by strain variability, local adaptation, and integration with cultural practices. Understanding these dynamics is crucial for optimizing the application of this approach in integrated pest management (IPM) systems and advancing sustainable cacao production.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".