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Invertebrate Neuropeptide Conference

2005· article· en· W1949789225 on OpenAlexaff
Stephen S. Tobe, Tippawan Singtripop, Thanit Pewnim, Ronald J. Nachman

Bibliographic record

VenueJournal of Insect Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsUniversity of Toronto
FundersNational Institutes of HealthBadan Riset dan Inovasi Nasional
KeywordsBiologyInvertebrateNeuropeptideMarine invertebratesZoologyEcologyBiochemistryReceptor

Abstract

fetched live from OpenAlex

Juvenile hormone plays a central role in the metamorphosis and reproduction of most insect species.The biosynthesis of juvenile hormone within the corpora allata of insects is regulated by neuropeptides.Allatostatin neuropeptides are known to act as inhibitors of juvenile hormone biosynthesis Allatotropin may, in certain insects, act to stimulate JH biosynthesis.These neuropeptides act on a membrane receptor(s) of the corpora allata that activates signal transduction pathway(s).This activation ultimately serves to regulate enzymes in the biosynthetic pathway that converts acetyl CoA to the sesquiterpenoids.Farnesoic acid o-methyltransferase (FAMeT) catalyzes the S-adenosylmethionine dependent conversion of Farnesoic acid to methylfarnesoic acid.It is thought that FAMeT may play a rate-limiting role in juvenile hormone biosynthesis in insects.FAMeT has been identified in the crustaceans, Metapenaeus ensis (shrimp) and Homarus americanus (Lobster).A database search based on sequence identity with crustacean FAMeT has revealed a putative gene product in Drosophila melanogaster.In order to characterize the putative Drosophila FAMeT ortholog's role in juvenile hormone biosynthesis we have analyzed the protein distribution, activity and in vivo expression.

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: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.011

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 head0.052
GPT teacher head0.230
Teacher spread0.178 · 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
GenreOther

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

Citations96
Published2005
Admission routes1
Has abstractyes

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