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Record W3084865494 · doi:10.3389/fgene.2020.01027

Diversity of Insect Sesquiterpenoid Regulation

2020· review· en· W3084865494 on OpenAlexaff
Stacey S.K. Tsang, Sean T.S. Law, Chade Li, Zhe Qu, William G. Bendena, Stephen S. Tobe, Jerome H. L. Hui

Bibliographic record

VenueFrontiers in Genetics · 2020
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of TorontoQueen's University
FundersChinese University of Hong Kong
KeywordsJuvenile hormoneBiologyEusocialityMetamorphosisInsectSexual dimorphismEvolutionary biologyEcologyZoologyLarvaHymenoptera

Abstract

fetched live from OpenAlex

Insects are arguably the most successful group of animals in the world in terms of both species numbers and diverse habitats. The sesquiterpenoids juvenile hormone, methyl farnesoate, and farnesoic acid are well known to regulate metamorphosis, reproduction, sexual dimorphism, eusociality, and defense in insects. Nevertheless, different insects have evolved with different sesquiterpenoid biosynthetic pathway as well as products. On the other hand, non-coding RNAs such as microRNAs have been implicated in regulation of many important biological processes, and have recently been explored in the regulation of sesquiterpenoid production. In this review, we summarize the latest findings on the diversity of sesquiterpenoids reported in different groups of insects, as well as the recent advancements in the understanding of regulation of sesquiterpenoid production by microRNAs.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.093
GPT teacher head0.324
Teacher spread0.230 · 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
GenreReview

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

Citations63
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in GeneticsSame topicNeurobiology and Insect Physiology ResearchFrench-language works237,207