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Record W2469511355 · doi:10.1093/hmg/ddw196

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

2016· article· en· W2469511355 on OpenAlexaff
Jennifer B. Permuth, Ailith Pirie, Y. Ann Chen, Hui‐Yi Lin, Brett M. Reid, Zhihua Chen, Álvaro N.A. Monteiro, Joe Dennis, Gustavo Mendoza-Fandiño, Hoda Anton‐Culver, Elisa V. Bandera, Maria Bisogna, Louise A. Brinton, Angela Brooks‐Wilson, Michael E. Carney, Georgia Chenevix‐Trench, Linda S. Cook, Daniel W. Cramer, Julie M. Cunningham, Cezary Cybulski, Aimee A. D’Aloisio, Jennifer A. Doherty, Madalene A. Earp, Robert P. Edwards, Brooke L. Fridley, Simon A. Gayther, Aleksandra Gentry‐Maharaj, Marc T. Goodman, Jacek Gronwald, Estrid Høgdall, Edwin S. Iversen, Anna Jakubowska, Allan Jensen, Beth Y. Karlan, Linda E. Kelemen, Suzanne K. Kjaer, Peter Kraft, Nhu D. Le, Douglas A. Levine, Jolanta Lissowska, Jan Lubiński, Keitaro Matsuo, Usha Menon, Rosemary Modugno, Kirsten B. Moysich, Toru Nakanishi, Roberta B. Ness, Sara H. Olson, Irene Orlow, Celeste Leigh Pearce, Tanja Pejović, Elizabeth M. Poole, Susan J. Ramus, Mary Anne Rossing, Dale P. Sandler, Xiao‐Ou Shu, Honglin Song, Jack A. Taylor, Soo‐Hwang Teo, Kathryn L. Terry, Pamela J. Thompson, Shelley S. Tworoger, Penelope M. Webb, Nicolas Wentzensen, Lynne R. Wilkens, Stacey J. Winham, Yin Ling Woo, Anna H. Wu, Hannah Yang, Wei Zheng, Argyrios Ziogas, Catherine M. Phelan, Joellen M. Schildkraut, Andrew Berchuck, Ellen L. Goode, Paul D.P. Pharoah, Thomas A. Sellers

Bibliographic record

VenueHuman Molecular Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
FundersMedical Research and Materiel CommandNational Center for Research ResourcesMedical Research CouncilNational Institutes of HealthMinistry of Health, Labour and WelfareNational Cancer InstituteUniversity College LondonLon V. Smith FoundationNational Institute for Health and Care ResearchNational Health and Medical Research CouncilMinnesota Ovarian Cancer AllianceUniversity of CambridgeCancer Research UKMayo Foundation for Medical Education and ResearchFrancis Crick InstituteRutgers Cancer Institute of New JerseyU.S. Department of DefenseOregon Health and Science UniversityPomorski Uniwersytet Medyczny W SzczecinieOak Foundation
KeywordsBiologyGenotypingExomeMissense mutationExome sequencingLinkage disequilibriumGeneticsOvarian cancerMinor allele frequencyGermline mutationGermlineAllele frequencyGeneCancerAlleleMutationGenotypeSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

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 score0.671
Threshold uncertainty score0.796

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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

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