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GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer
Paul D.P. Pharoah, Ya-Yu Tsai, Susan J. Ramus, Catherine M. Phelan, Ellen L. Goode, Kate Lawrenson, Melissa A. Buckley, Brooke L. Fridley, Jonathan P. Tyrer, Howard C. Shen, Rachel Palmieri Weber, Rod Karevan, Melissa C. Larson, Honglin Song, Daniel C. Tessier, François Bacot, Daniel Vincent, Julie M. Cunningham, Joe Dennis, Ed Dicks, Katja K.H. Aben, Hoda Anton‐Culver, Natalia Antonenkova, Sebastian M. Armasu, Laura Baglietto, Elisa V. Bandera, Matthias W. Beckmann, Michael J. Birrer, Greg Bloom, Natalia Bogdanova, James D. Brenton, Louise A. Brinton, Angela Brooks‐Wilson, Robert Brown, Ralf Bützow, Ian Campbell, Michael E. Carney, Renato S. Carvalho, Jenny Chang‐Claude, Y Anne Chen, Zhihua Chen, Wong‐Ho Chow, Mine Cicek, Gerhard A. Coetzee, Linda S. Cook, Daniel W. Cramer, Cezary Cybulski, Agnieszka Dansonka‐Mieszkowska, Evelyn Despierre, Jennifer A. Doherty, Thilo Dörk, Andreas du Bois, Matthias Dürst, Diana Eccles, Robert P. Edwards, Arif B. Ekici, Peter A. Fasching, David Fenstermacher, James M. Flanagan, Yu-Tang Gao, Montserrat García‐Closas, Aleksandra Gentry‐Maharaj, Graham G. Giles, Anxhela Gjyshi, Martin Gore, Jacek Gronwald, Qi Guo, Mari K. Halle, Philipp Harter, Alexander Hein, Florian Heitz, Peter Hillemanns, Maureen E. Hoatlin, Estrid Høgdall, Claus Høgdall, Satoyo Hosono, Anna Jakubowska, Allan Jensen, Kimberly R. Kalli, Beth Y. Karlan, Linda E. Kelemen, Lambertus A. Kiemeney, Susanne K. Kjær, Gottfried E. Konecny, Camilla Krakstad, Jolanta Kupryjańczyk, Diether Lambrechts, Sandrina Lambrechts, Nhu D. Le, Nathan Lee, Janet Lee, Arto Leminen, Boon Kiong Lim, Jolanta Lissowska, Jan Lubiński, Lene Lundvall, Galina Lurie, Leon F.A.G. Massuger, Keitaro Matsuo, Valerie McGuire, Usha Menon, Francesmary Modugno, Kirsten B. Moysich, Toru Nakanishi, Steven A. Narod, Roberta B. Ness, Heli Nevanlinna, Stefan Nickels, Houtan Noushmehr, Kunle Odunsi, Sara H. Olson, Irene Orlow, James Paul, Tanja Pejović, Liisa M. Pelttari, Jenny Permuth‐Wey, Malcolm C. Pike, Elizabeth M. Poole, Xiaotao Qu, Harvey A. Risch, Lorna Rodríguez-Rodríguez, Mary Anne Rossing, Anja Rudolph, Ingo B. Runnebaum, Iwona K. Rzepecka, Helga B. Salvesen, Ira Schwaab, Gianluca Severi, Hui Shen, Vijayalakshmi Shridhar, Xiao‐Ou Shu, Weiva Sieh, Melissa C. Southey, Paul T. Spellman, Kazuo Tajima, Soo‐Hwang Teo, Kathryn L. Terry, Pamela J. Thompson, Agnieszka Timorek, Shelley S. Tworoger, Anne M. van Altena, David Van Den Berg, Ignace Vergote, Robert A. Vierkant, Allison F. Vitonis, Shan Wang‐Gohrke, Nicolas Wentzensen, Alice S. Whittemore, Elisabeth Wik, Boris Winterhoff, Yin Ling Woo, Anna H. Wu, Hannah Yang, Wei Zheng, Argyrios Ziogas, Famida Zulkifli, Marc T. Goodman, Per Hall, Douglas F. Easton, Celeste Leigh Pearce, Andrew Berchuck, Georgia Chenevix‐Trench, Edwin S. Iversen, Álvaro N.A. Monteiro, Simon A. Gayther, Joellen M. Schildkraut, Thomas A. Sellers
Bibliographic record
VenueNature Genetics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of TorontoBC Cancer AgencyPublic Health OntarioMcGill University and Génome Québec Innovation CentreMcGill University Health CentreWomen's College HospitalAlberta Health ServicesUniversity of CalgaryMcGill University
FundersDavid Geffen School of Medicine, University of California, Los AngelesNational Cancer InstituteUniversity Hospital Southampton NHS Foundation TrustAudrey and Theodor Geisel School of Medicine at DartmouthHaukeland UniversitetssjukehusDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of PittsburghDartmouth CollegeDeutsches KrebsforschungszentrumPomorski Uniwersytet Medyczny W SzczecinieRigshospitaletUniversitetet i BergenPeter MacCallum Cancer CentreUniversity of SouthamptonWellcome TrustUniversity of Southern CaliforniaCancer Research UKHerlev HospitalEuropean CommissionMagee-Womens Research InstituteMedizinischen Hochschule HannoverMonash UniversityBrigham and Women's HospitalUniversitätsklinikum JenaUniversity of PittsburghOvarian Cancer Research Fund
KeywordsBiologyGenome-wide association studyOvarian cancerReplication (statistics)GeneticsComputational biologyMeta-analysisCancerSingle-nucleotide polymorphismInternal medicineVirologyGeneGenotype
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 head0.034
GPT teacher head0.322
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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 designMeta-analysis
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
Citations361
Published2013
Admission routes1
Has abstractno