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Record W7134986242 · doi:10.5376/me.2024.15.0026

Insights into Mechanisms of Maize Resistance to Major Pests

2024· article· W7134986242 on OpenAlexvenueno aff
Jiamin Wang, Yunchao Huang

Bibliographic record

VenueMolecular Entomology · 2024
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)Zea maysPlant disease resistanceInsecticide resistanceAdaptability

Abstract

fetched live from OpenAlex

Maize is a critical staple crop, providing food security and supporting economies worldwide. However, the crop faces persistent threats from various pests, leading to significant yield losses and environmental damage. This study explores the mechanisms of maize resistance to major pests, encompassing conventional breeding strategies, biochemical defenses, genetic and molecular tools, and anatomical traits. A case study on Bt maize highlights its role as a breakthrough in pest resistance, delving into its development, mechanisms of action, and socioeconomic impacts. Additionally, integrative approaches combining genetic, agronomic, and biological practices are discussed to enhance pest resistance. Challenges such as resistance evolution, regulatory hurdles, and the need for sustainable solutions are examined. The findings underscore the necessity of continuous innovation in breeding techniques and integrative pest management to ensure long-term maize productivity and sustainability.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.241
Teacher spread0.232 · 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 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

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