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Record W2036959160 · doi:10.1172/jci38420

Hoofbeats, zebras, and insights into insulin resistance

2009· letter· en· W2036959160 on OpenAlexafffund
Robert A. Hegele, Karen Reue

Bibliographic record

VenueJournal of Clinical Investigation · 2009
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsRobarts Clinical TrialsWestern University
FundersRobarts Research InstituteU.S. Public Health ServiceNational Institutes of HealthOntario Genomics InstituteOntario GenomicsGenome CanadaHeart and Stroke Foundation of CanadaPfizer
KeywordsAKT2PhenotypeBiologyInsulin resistanceInsulin receptorGluconeogenesisGeneticsSerineInsulinGeneSignal transductionPhosphorylationPI3K/AKT/mTOR pathwayEndocrinologyAKT1

Abstract

fetched live from OpenAlex

In this issue of the JCI, Semple and colleagues report phenotypic evaluation of patients with a germline mutation in the gene encoding serine/threonine kinase AKT2 (see the related article beginning on page 315). Their findings support the idea that the postreceptor actions of insulin in the liver--suppression of gluconeogenesis and stimulation of lipogenesis--are mediated through divergent pathways that can be uncoupled. The results appear to refine the arrangement of crucial steps along these pathways and show how comprehensive study of the phenotype, "deep phenotyping," of patients who carry rare mutations might complement other types of experiments to elucidate complex pathways and mechanisms.

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)0.001
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.013
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0130.016
Insufficient payload (model declined to judge)0.0030.002

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 head0.033
GPT teacher head0.324
Teacher spread0.291 · 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
GenreCommentary

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

Citations4
Published2009
Admission routes2
Has abstractyes

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