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Record W2004509917 · doi:10.1002/humu.21008

Genomic variation in a global village: Report of the 10th annual Human Genome Variation Meeting 2008

2009· article· en· W2004509917 on OpenAlexafffundabout
Anthony J. Brookes, Stephen J. Chanock, Thomas J. Hudson, Leena Peltonen, Gonçalo R. Abecasis, Pui–Yan Kwok, Stephen W. Scherer

Bibliographic record

VenueHuman Mutation · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsSickKids FoundationHospital for Sick ChildrenInstitute of Cancer ResearchOntario Institute for Cancer Research
FundersNational Human Genome Research InstituteCanadian Institutes of Health ResearchGenome CanadaOntario Ministry of Research and InnovationCanadian Institute for Advanced Research
KeywordsHumBiologyVariation (astronomy)GenomicsHuman genomeScope (computer science)Copy-number variationGenomeSingle-nucleotide polymorphismPersonal genomicsLibrary scienceGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

The Centre for Applied Genomics of the Hospital for Sick Children and the University of Toronto hosted the 10th Human Genome Variation (HGV) Meeting in Toronto, Canada, in October 2008, welcoming about 240 registrants from 34 countries. During the 3 days of plenary workshops, keynote address, and poster sessions, a strong cross-disciplinary trend was evident, integrating expertise from technology and computation, through biology and medicine, to ethics and law. Single nucleotide polymorphisms (SNPs) as well as the larger copy number variants (CNVs) are recognized by ever-improving array and next-generation sequencing technologies, and the data are being incorporated into studies that are increasingly genome-wide as well as global in scope. A greater challenge is to convert data to information, through databases, and to use the information for greater understanding of human variation. In the wake of publications of the first individual genome sequences, an inaugural public forum provided the opportunity to debate whether we are ready for personalized medicine through direct-to-consumer testing. The HGV meetings foster collaboration, and fruits of the interactions from 2008 are anticipated for the 11th annual meeting in September 2009.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2009
Admission routes3
Has abstractyes

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