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Record W2113368041 · doi:10.1093/nar/gkn939

The HuRef Browser: a web resource for individual human genomics

2008· article· en· W2113368041 on OpenAlexfundno aff
Nelson Axelrod, Pauline C. Ng, Timothy B. Stockwell, Jonathan Crabtree, Jiaqi Huang, Ewen F. Kirkness, Robert L. Strausberg, M.E. Frazier, J. Craig Venter, Saul Kravitz, Samuel Lévy

Bibliographic record

VenueNucleic Acids Research · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsGenome browserEnsemblBiologyGenomeContext (archaeology)GenomicsHuman genomeReference genomeComparative genomicsComputational biologyWeb browserIndelStructural variationGeneticsWorld Wide WebThe InternetComputer scienceSingle-nucleotide polymorphismGene

Abstract

fetched live from OpenAlex

The HuRef Genome Browser is a web application for the navigation and analysis of the previously published genome of a human individual, termed HuRef. The browser provides a comparative view between the NCBI human reference sequence and the HuRef assembly, and it enables the navigation of the HuRef genome in the context of HuRef, NCBI and Ensembl annotations. Single nucleotide polymorphisms, indels, inversions, structural and copy-number variations are shown in the context of existing functional annotations on either genome in the comparative view. Demonstrated here are some potential uses of the browser to enable a better understanding of individual human genetic variation. The browser provides full access to the underlying reads with sequence and quality information, the genome assembly and the evidence supporting the identification of DNA polymorphisms. The HuRef Browser is a unique and versatile tool for browsing genome assemblies and studying individual human sequence variation in a diploid context. The browser is available online at http://huref.jcvi.org.

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)0.002
metaresearch head score (Gemma)0.003
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: Software · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0970.051

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 head0.070
GPT teacher head0.333
Teacher spread0.263 · 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
GenreSoftware

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

Citations13
Published2008
Admission routes1
Has abstractyes

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