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Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer
Stig E. Bojesen, Karen A. Pooley, Sharon E. Johnatty, Jonathan Beesley, Kyriaki Michailidou, Jonathan P. Tyrer, Stacey L. Edwards, Hilda A. Pickett, Howard C. Shen, Chanel E. Smart, Kristine M. Hillman, Kate Lawrenson, Michael D. Stutz, Yi Lu, Rod Karevan, Nicholas T. Woods, Rebecca L. Johnston, Juliet D. French, Maren Weischer, Sune F. Nielsen, Melanie Maranian, Maya Ghoussaini, Shahana Ahmed, Caroline Baynes, Manjeet K. Bolla, Qin Wang, Joe Dennis, Lesley McGuffog, Daniel Barrowdale, Andrew Lee, Sue Healey, Michael Lush, Daniel C. Tessier, Daniel Vincent, Françis Bacot, Ignace Vergote, Sandrina Lambrechts, Evelyn Despierre, Harvey A. Risch, Anna González‐Neira, Mary Anne Rossing, Guillermo Pita, Jennifer A. Doherty, Núria Álvarez, Melissa C. Larson, Brooke L. Fridley, Nils Schoof, Jenny Chang‐Claude, Mine Cicek, Julian Peto, Kimberly R. Kalli, Annegien Broeks, Sebastian M. Armasu, Marjanka K. Schmidt, Linde M. Braaf, Boris Winterhoff, Heli Nevanlinna, Gottfried E. 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Bibliographic record
VenueNature Genetics · 2013
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversité de MontréalUniversity Health NetworkMount Sinai HospitalLunenfeld-Tanenbaum Research InstituteUniversity of CalgaryBC Cancer AgencyAlberta Health ServicesUniversité LavalMcGill UniversitySimon Fraser UniversityWomen's College HospitalRoyal Victoria HospitalCentre hospitalier universitaire de QuébecUniversity of TorontoPublic Health OntarioMcGill University and Génome Québec Innovation Centre
FundersNational Institute for Health and Care ResearchCanadian Institutes of Health ResearchEuropean CommissionNational Cancer InstituteCancer Research UKWellcome Trust
KeywordsBiologyTelomereLocus (genetics)Breast cancerGeneticsOvarian cancerCancerGene
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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.008
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 head0.017
GPT teacher head0.266
Teacher spread0.249 · 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
Citations540
Published2013
Admission routes2
Has abstractno