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Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA
Madalene A. Earp, Linda E. Kelemen, Anthony M. Magliocco, Kenneth D. Swenerton, Georgia Chenevix‐Trench, Yi Lu, Alexander Hein, Arif B. Ekici, Matthias W. Beckmann, Peter A. Fasching, Diether Lambrechts, Evelyn Despierre, Ignace Vergote, Sandrina Lambrechts, Jennifer A. Doherty, Mary Anne Rossing, Jenny Chang‐Claude, Anja Rudolph, Grace Friel, Kirsten B. Moysich, Kunle Odunsi, Lara Sucheston‐Campbell, Galina Lurie, Marc T. Goodman, Michael E. Carney, Pamela J. Thompson, Ingo B. Runnebaum, Matthias Dürst, Peter Hillemanns, Thilo Dörk, Natalia Antonenkova, Natalia Bogdanova, Arto Leminen, Heli Nevanlinna, Liisa M. Pelttari, Ralf Bützow, Clareann H. Bunker, Francesmary Modugno, Robert P. Edwards, Roberta B. Ness, Andreas du Bois, Florian Heitz, Ira Schwaab, Philipp Harter, Beth Y. Karlan, Christine Walsh, Jenny Lester, Allan Jensen, Susanne K. Kjær, Claus Høgdall, Estrid Høgdall, Lene Lundvall, Thomas A. Sellers, Brooke L. Fridley, Ellen L. Goode, Julie M. Cunningham, Robert A. Vierkant, Graham G. Giles, Laura Baglietto, Gianluca Severi, Melissa C. Southey, Dong Liang, Xifeng Wu, Karen H. Lu, Michelle A.T. Hildebrandt, Douglas A. Levine, Maria Bisogna, Joellen M. Schildkraut, Edwin S. Iversen, Rachel Palmieri Weber, Andrew Berchuck, Daniel W. Cramer, Kathryn L. Terry, Elizabeth M. Poole, Shelley S. Tworoger, Elisa V. Bandera, Urmila Chandran, Irene Orlow, Sara H. Olson, Elisabeth Wik, Helga B. Salvesen, Line Bjørge, Mari K. Halle, Anne M. van Altena, Katja K.H. Aben, Lambertus A. Kiemeney, Leon F.A.G. Massuger, Tanja Pejović, Yukie T. Bean, Cezary Cybulski, Jacek Gronwald, Jan Lubiński, Nicolas Wentzensen, Louise A. Brinton, Jolanta Lissowska, Montserrat García‐Closas, Ed Dicks, Joe Dennis, Douglas F. Easton, Honglin Song, Jonathan P. Tyrer, Paul D.P. Pharoah, Diana Eccles, Ian Campbell, Alice S. Whittemore, Valerie McGuire, Weiva Sieh, Joseph H. Rothstein, James M. Flanagan, James Paul, Robert Brown, Catherine M. Phelan, Harvey A. Risch, Steven A. Narod, Argyrios Ziogas, Hoda Anton‐Culver, Aleksandra Gentry‐Maharaj, Usha Menon, Simon A. Gayther, Susan J. Ramus, Anna H. Wu, Celeste Leigh Pearce, Malcolm C. Pike, Agnieszka Dansonka‐Mieszkowska, Iwona K. Rzepecka, Lukasz M. Szafron, Jolanta Kupryjańczyk, Linda S. Cook, Nhu D. Le, Angela Brooks‐Wilson
Bibliographic record
VenueHuman Genetics · 2013
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsWomen's College HospitalUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of British ColumbiaUniversity of CalgaryCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
FundersNational Center for Research ResourcesCancer Council VictoriaCancer Council South AustraliaNational Cancer InstituteHelse VestCancer Council TasmaniaNational Institutes of HealthCancer Council NSWCancer Research UKRutgers Cancer Institute of New JerseyWorkSafeBCBundesministerium für Bildung und ForschungLon V. Smith FoundationDeutsches KrebsforschungszentrumHelsingin ja Uudenmaan SairaanhoitopiiriCanadian Institutes of Health ResearchCancer Council QueenslandFred C. and Katherine B. Andersen Foundation
KeywordsGenome-wide association studySerous fluidBiologyOdds ratioGenotypeOvarian cancerAlleleGenetic associationOncologyEpithelial ovarian cancerCase-control studyGeneticsInternal medicineCancerGeneSingle-nucleotide polymorphismMedicine
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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 head0.286
Teacher spread0.251 · 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 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
Citations26
Published2013
Admission routes2
Has abstractno