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Record W4402695740 · doi:10.5376/jmr.2024.14.0013

Impact of Genetic Control Techniques on Mosquito Populations

2024· article· en· W4402695740 on OpenAlexvenueno aff
Wenfei Zhang

Bibliographic record

VenueJournal of Mosquito Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenetics

Abstract

fetched live from OpenAlex

Mosquito populations pose significant global public health challenges due to their role in transmitting diseases such as malaria, dengue, and Zika. Controlling mosquito populations is thus critical for reducing these health impacts. This study explores various genetic control techniques, including the Sterile Insect Technique (SIT), Release of Insects carrying a Dominant Lethal (RIDL), gene drive systems, and Wolbachia -based strategies. Through detailed case studies from Brazil, Africa, and Australia, this study examines the mechanisms of action, including genetic modification, population suppression, and population replacement; additionally, analyzes the ecological and evolutionary impacts, discussing potential benefits and risks. To fully understand the challenges and opportunities in implementing these technologies, this study also explores ethical, social, and regulatory considerations. Our findings underscore the importance of advancing genetic control technologies and addressing associated challenges to improve public health outcomes. This study concludes with a summary of key points, implications for public health, and future research directions.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.449
Teacher spread0.391 · 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 designBench or experimental
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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