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Record W2071404615 · doi:10.1038/npre.2008.1784.2

Suggested actions from the Melbourne HVP Information Seminar

2008· preprint· en· W2071404615 on OpenAlexaff
Richard G.H. Cotton, Myles Axton, Agnes Bankier, Bernard Brais, Lawrence Cavedon, Desirée du Sart, Peter George, David E. Goldgar, Terence Harrison, Marienne Hibbert, John L. Hopper, Finlay Macrae, Christine M. O’Keefe, David Ravine, Ravi Savarirayan, L. J. Sheffield, Tim Staunton Smith, Nicola Stokes, Vijaya Sundararajan, David R. Thorburn, Ingrid Winship

Bibliographic record

VenueNature Precedings · 2008
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsUniversité de MontréalHôpital Notre-Dame
Fundersnot available
KeywordsLibrary sciencePolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract The Human Variome Project (HVP; www.humanvariomeproject.org) was initiated at a meeting in June 2006 and addressed the problems of collecting genetic information and generated 96 recommendations (http://www.nature.com/ng/journal/v39/n4/full/ng0407-423.html) to overcome these, with the focus on Mendelian disease. A considerable number of projects have been added, to those that have been ongoing for a number of years, since that meeting. Also, a planning meeting is to be held May 25-29, 2008 in Spain (http://www.humanvariomeproject.org/HVP2008/).A dramatic boost has been given to the HVP by the preparedness and action of the International Society for Gastrointestinal Hereditary Tumours (InSiGHT; www.insight-group.org), to, in order to improve their own informatics systems for dealing with inherited colon cancer, set up a pilot system for collection and databasing mutation and phenotype information, i.e. to act as pilot for the HVP. This is then intended to be transferred to other genes and countries. Much relevant activity in this project is being led from and is based in Melbourne.This meeting in Melbourne has been conceived to review the current local situation and plans for the future. We are privileged that Myles Axton, Editor of Nature Genetics, a strong supporter of the HVP (see April 2007 Nature Genetics Editorial) and who has some ideas in the area (see August 2007 Nature Genetics Editorial) agreed to be keynote speaker.We proposed that the output of this meeting be published and, with permission, the abstracts and presentations placed on the website (www.humanvariomeproject.org/?p=Melbourne_Meeting). We also hope it will inform the May HVP Planning Meeting.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0020.002
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 head0.016
GPT teacher head0.284
Teacher spread0.269 · 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.

Study designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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