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INTEGRATED PEST MANAGEMENT AND ENTOMOPATHOGENIC FUNGAL BIOTECHNOLOGY IN THE LATIN AMERICAS: I-OPPORTUNITIES IN A GLOBALAGRICULTURE

2024· article· en· W4401105950 on OpenAlexaff
Edison Valencia, George G. Khachatourians

Bibliographic record

VenueRevista de la Academia Colombiana de Ciencias Exactas Físicas y Naturales · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCommercializationIntegrated pest managementEntomopathogenic fungiAgroforestryEcologyBiologyBiological pest controlBusiness

Abstract

fetched live from OpenAlex

Entomopathogenic fungi (EPF) have been used as insect biocontrol agents separately and in integrated pest management (1PM) worldwide including in the Latin Americas. The proper use of these agents along with other elements and concepts of 1PM has significant impact on the provision of crops. fruits and other agricultura! products Entomopathogenic fungi can play a significant role in the preservation of the natural delicate balance of beneficia! biota and their active spreading from the surrounding natural habitats, such as the tropical rain forest, the humid cloudy forest in the Andes and other important ecosystems, to the agricultura} lands in Central and South America. Of ali known EPF, there are only about half a dozen for which prerequisite aspects of fungal biotechnology for industrial R and D are in place. Because of its precedent setting leadership in the use ofEPF in 1PM and agroecological practices, LatinAmerica stands to gain irnrnensely here and more so if the concept of rational design of bioinsecticides (RADBIO) is employed. The future prospects will depend on a balance of discovery research coupled to a strong and dependable industrialization effort to develop the framework for illustrating public acceptance, commercialization potential and widespread use of EPF in 1PM. The potential for the next generation of mycoinsecticides is now loorning on the horizon.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.248
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueRevista de la Academia Colombiana de Ciencias Exactas Físicas y NaturalesSame topicEntomopathogenic Microorganisms in Pest ControlFrench-language works237,207