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Record W7119539644 · doi:10.5281/zenodo.3408355

Summary statistics for the InsPIRE consortium (pancreatic islets eQTLs)

2019· dataset· W7119539644 on OpenAlexafffund
Ana Viñuela, Arushi Varshney, Rashmi B. Prasad, Olof Asplund, Amanda Bennett, Michael Boehnke, Andrew Brown, Michael Erdos, João Fadista, Ola Hansson, Gad Hatem, Cédric Howald, Apoorva K. Iyengar, Paul Johnson, Ulrika Krus, Patrick E. MacDonald, Anubha Mahajan, Jocelyn E. Manning Fox, Narisu Narisu, Vibe Nylander, Peter Orchard, NIkolaos I. Panousis, A. J. Payne, Michael Stitzel, Swarooparani Vadlamudi, Ryan Welch, Francis S. Collins, Karen Mohlke, Anna Gloyn, Emmanouil Dermitzakis, Leif Groop, Stephen Parker

Bibliographic record

VenueDiscovery Research Portal (University of Dundee) · 2019
Typedataset
Language
Field
Topic
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesMedical Research CouncilAlberta Diabetes FoundationVetenskapsrådetNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungEuropean CommissionNovo NordiskNational Institute for Health and Care ResearchNational Human Genome Research InstituteWellcome TrustUniversity of OxfordStiftelsen för Strategisk ForskningEuropean Foundation for the Study of DiabetesAstraZenecaCanadian Institutes of Health ResearchAmerican Diabetes Association
KeywordsPancreatic isletsSummary statisticsIsletGene expressionExpression (computer science)Gene

Abstract

fetched live from OpenAlex

Summary statistics for the InsPIRE study: Influence of genetic variants on gene expression in human pancreatic islets – implications for type 2 diabetes This datasets includes eQTLs from 420 pancreatic islets (exon and gene level quantifications) and 27 beta-cells FAC sorted (exon quantifications) form RNA-Seq samples. Full summary statistics and independent associations are included. The full description of methods is currently available here: Bioxiv (https://www.biorxiv.org/content/10.1101/655670v1).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0030.011
Scholarly communication0.0010.003
Open science0.0080.005
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0060.007

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 head0.087
GPT teacher head0.345
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2019
Admission routes2
Has abstractyes

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