MétaCan
Menu
Back to cohort
Record W2163150133 · doi:10.1186/1471-2156-6-s1-s1

Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans

2005· article· en· W2163150133 on OpenAlexaff
Joan E. Bailey‐Wilson, Laura Almasy, Mariza de Andrade, Julia N. Bailey, Heike Bickeböller, Heather J. Cordell, E. Warwick Daw, Lynn R. Goldin, Ellen L. Goode, Courtney Gray‐McGuire, Wayne A. Hening, Gail P. Jarvik, Brion S. Maher, Nancy R. Mendell, Andrew D. Paterson, John P. Rice, Glen A. Satten, Brian K. Suarez, Veronica J. Vieland, Marsha Wilcox, Heping Zhang, Andreas Ziegler, Jean W. MacCluer

Bibliographic record

VenueBMC Genetics · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsHospital for Sick Children
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Institute of Mental Health
KeywordsMicrosatelliteSingle-nucleotide polymorphismGeneticsBiologyGenetic markerGenomeGenome ScanComputational biologyGenotypeAlleleGene

Abstract

fetched live from OpenAlex

This supplement to BMC Genetics contains the proceedings of the Genetic Analysis Workshop 14 (GAW14), which was held September 7-10, 2004, in Noordwijkerhout, The Netherlands. These workshops have been held since 1982 and now are held biennially. They serve as a forum for statisticians, epidemiologists, geneticists, and other scientists interested in these fields to introduce novel statistical methods and to evaluate and compare novel and existing methods. At each GAW, an existing dataset is selected, and a set of simulated data is devised such that statistical questions of wide and current interest may be addressed. These data are made available to scien-tists worldwide who then report the results of their analyses of these data at the GAW meeting. GAW attendees must submit an analysis of one of these datasets, or be a workshop organizer or a dataset provider. The purpose of these workshops is to allow the comparison of statistical methodologies for genetic epidemiology using the same, well-described datasets. More information about GAW, including details of upcoming workshops, may be found at http://www.gaworkshop.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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 designBench or experimental
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

Citations12
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueBMC GeneticsSame topicMolecular Biology Techniques and ApplicationsFrench-language works237,207