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Record W2068451800 · doi:10.1074/jbc.r300021200

Three-dimensional Structural Interactions of Insulin and Its Receptor

2003· review· en· W2068451800 on OpenAlexaff
Cecil C. Yip, Peter Ottensmeyer

Bibliographic record

VenueJournal of Biological Chemistry · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsInsulin receptorInsulinReceptorBiophysicsTransmembrane proteinChemistryLigand (biochemistry)Cell biologyBiologyBiochemistryEndocrinologyInsulin resistance

Abstract

fetched live from OpenAlex

Electron microscopic imaging of the large insulin receptor protein in complex with insulin and in its free form, coupled with three-dimensional reconstruction and fitting of atomic subdomains, has yielded a structural model that permits an understanding of insulin binding at the atomic level. The model corroborates and explains the biological activity and binding behavior of virtually all naturally occurring insulins and insulin analogues, as well as the effects of receptor mutations on insulin binding. The model also provides a basis to address the fundamental question on the mechanism of transmembrane activation of receptors by ligand binding.

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 score0.001
Threshold uncertainty score0.007

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.029
GPT teacher head0.306
Teacher spread0.277 · 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

Citations48
Published2003
Admission routes1
Has abstractyes

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