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Assessing the genetic architecture of epithelial ovarian cancer histological subtypes
Gabriel Cuéllar-Partida, Yi Lu, Suzanne C. Dixon‐Suen, Peter A. Fasching, Alexander Hein, Stefanie Burghaus, Matthias W. Beckmann, Diether Lambrechts, Els Van Nieuwenhuysen, Ignace Vergote, Adriaan Vanderstichele, Jennifer A. Doherty, Mary Anne Rossing, Jenny Chang‐Claude, Anja Rudolph, Shan Wang‐Gohrke, Marc T. Goodman, Natalia Bogdanova, Thilo Dörk, Matthias Dürst, Peter Hillemanns, Ingo B. Runnebaum, Natalia Antonenkova, Ralf Bützow, Arto Leminen, Heli Nevanlinna, Liisa M. Pelttari, Robert P. Edwards, Joseph L. Kelley, Francesmary Modugno, Kirsten B. Moysich, Roberta B. Ness, Rikki Cannioto, Estrid Høgdall, Claus Høgdall, Allan Jensen, Graham G. Giles, Fiona Bruinsma, Susanne K. Kjær, Michelle A.T. Hildebrandt, Dong Liang, Karen H. Lu, Xifeng Wu, Maria Bisogna, Fanny Dao, Douglas A. Levine, Daniel W. Cramer, Kathryn L. Terry, Shelley S. Tworoger, Meir J. Stampfer, Stacey A. Missmer, Line Bjørge, Helga B. Salvesen, Reidun Kristin Kopperud, Katharina Bischof, Katja K.H. Aben, Lambertus A. Kiemeney, Leon F.A.G. Massuger, Angela Brooks‐Wilson, Sara H. Olson, Valerie McGuire, Joseph H. Rothstein, Weiva Sieh, Alice S. Whittemore, Linda S. Cook, Nhu D. Le, C. Blake Gilks, Jacek Gronwald, Anna Jakubowska, Jan Lubiński, Tomasz Kluz, Honglin Song, Jonathan P. Tyrer, Nicolas Wentzensen, Louise A. Brinton, Britton Trabert, Jolanta Lissowska, Steven A. Narod, Catherine Phelan, Hoda Anton‐Culver, Argyrios Ziogas, Diana Eccles, Ian Campbell, Simon A. Gayther, Aleksandra Gentry‐Maharaj, Usha Menon, Susan J. Ramus, Anna H. Wu, Agnieszka Dansonka‐Mieszkowska, Jolanta Kupryjańczyk, Agnieszka Timorek, Lukasz M. Szafron, Julie M. Cunningham, Brooke L. Fridley, Stacey J. Winham, Elisa V. Bandera, Elizabeth M. Poole, Terry K. Morgan, Ellen L. Goode, Joellen M. Schildkraut, Celeste Leigh Pearce, Andrew Berchuck, Paul D.P. Pharoah, Penelope M. Webb, Georgia Chenevix‐Trench, Harvey A. Risch, Stuart MacGregor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
Bibliographic record
VenueHuman Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsWomen's College HospitalUniversity of TorontoPublic Health OntarioUniversity of British ColumbiaCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
FundersMedical Research and Materiel CommandNational Center for Research ResourcesCanadian Institutes of Health ResearchFrancis Crick InstituteNational Cancer InstituteCancer Research UKCalifornia Breast Cancer Research ProgramNational Center for Advancing Translational SciencesFoundation for the National Institutes of Health
KeywordsBiologySerous fluidHeritabilityGenetic architectureOvarian cancerSingle-nucleotide polymorphismGeneticsCancerGenetic associationClear cellDiseaseOncologyQuantitative trait locusGenotypeInternal medicineGeneCarcinomaMedicine
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.
Full frame distilled prediction
Teacher imitationNot 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.727
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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 itQuick stats
Citations29
Published2016
Admission routes2
Has abstractno