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Record W4407557418 · doi:10.5376/me.2024.15.0010

Preventing the Spread of Colorado Potato Beetle: Strategies and Technologies

2024· article· en· W4407557418 on OpenAlexvenueno aff
Sibin Wang, Jia Xing, He Xian

Bibliographic record

VenueMolecular Entomology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
Fundersnot available
KeywordsColorado potato beetleBiologyAgroforestryPEST analysisHorticulture

Abstract

fetched live from OpenAlex

The Colorado Potato Beetle (CPB) is a serious pest in global agriculture, with its threat to potato crops becoming increasingly severe. This study explores the biology and behavior of CPB, including its life cycle, feeding habits, and the environmental factors influencing its spread. Traditional control methods, such as chemical pesticides, crop rotation, and biological control, have been effective to some extent but face challenges like the development of resistance and environmental impacts. To address these issues, modern strategies and technologies, such as Integrated Pest Management (IPM), genetic engineering, and precision agriculture, are being introduced and have shown significant success in practice. Through case studies, this study demonstrates the effectiveness and lessons learned from the implementation of these control strategies, discusses the potential threats posed by CPB, identifies research gaps, and explores future technological innovations. This study also provides recommendations for policy and practice, aiming to support the sustainable development of global 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

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