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Record W1991624054 · doi:10.1101/cshperspect.a009050

Receptor Tyrosine Kinases in Drosophila Development

2013· review· en· W1991624054 on OpenAlexfundno aff
Richelle Sopko, Norbert Perrimon

Bibliographic record

VenueCold Spring Harbor Perspectives in Biology · 2013
Typereview
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchHoward Hughes Medical Institute
KeywordsReceptor tyrosine kinaseBiologyROR1Receptor Protein-Tyrosine KinasesTyrosine kinaseTyrosine phosphorylationCell biologyProtein tyrosine phosphataseTyrosineJAK-STAT signaling pathwaySH2 domainProto-oncogene tyrosine-protein kinase SrcKinasePlatelet-derived growth factor receptorSignal transductionReceptorGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Tyrosine phosphorylation plays a significant role in a wide range of cellular processes. The Drosophila genome encodes more than 20 receptor tyrosine kinases and extensive studies in the past 20 years have illustrated their diverse roles and complex signaling mechanisms. Although some receptor tyrosine kinases have highly specific functions, others strikingly are used in rather ubiquitous manners. Receptor tyrosine kinases regulate a broad expanse of processes, ranging from cell survival and proliferation to differentiation and patterning. Remarkably, different receptor tyrosine kinases share many of the same effectors and their hierarchical organization is retained in disparate biological contexts. In this comprehensive review, we summarize what is known regarding each receptor tyrosine kinase during Drosophila development. Astonishingly, very little is known for approximately half of all Drosophila receptor tyrosine kinases.

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 score0.003
Threshold uncertainty score0.009

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.091
GPT teacher head0.369
Teacher spread0.278 · 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

Citations82
Published2013
Admission routes1
Has abstractyes

Explore more

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