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Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk
Robert E. Schoen, D. Timothy Bishop, Alicja Wolk, Temitope O. Keku, Virginia Díez‐Obrero, Hermann Brenner, Rui Chen, Konstantinos K. Tsilidis, Marc J. Gunter, Lori C. Sakoda, Akihisa Hidaka, Graham G. Giles, Tabitha A. Harrison, Yu Tian, Kristina M. Jordahl, Arif Budiarto, Michael O. Woods, Edward Ruiz-Narváez, Conghui Qu, Xuechen Chen, Stephen N. Thibodeau, Gad Rennert, Sonja I. Berndt, Kala Visvanathan, Daniel D. Buchanan, Li Hsu, Amit D. Joshi, Bethany Van Guelpen, Andrew T. Chan, Anita R. Peoples, Li Li, Yi Lin, Bens Pardamean, Eric S. Kawaguchi, Peter T. Campbell, Fränzel J.B. van Duijnhoven, Andrew J. Pellatt, W. James Gauderman, Hongmei Nan, Volker Arndt, Ulrike Peters, Michael Hoffmeister, Jennifer Ose, Jenny Chang‐Claude, Ross L. Prentice, Susanna C. Larsson, Shuji Ogino, Rami Nassir, Steven Gallinger, Vı́ctor Moreno, Jane C. Figueiredo, Mireia Obón‐Santacana, James W. Baurley, Anshul Kundaje, Duncan C. Thomas, Juan Pablo Lewinger, Sophia Harlid, Elizabeth A. Platz, Robert Carreras‐Torres, Anna H. Wu, David V. Conti, Mark A. Jenkins, Yu‐Ru Su, David A. Drew, Andre E. Kim, Neil Murphy, Loı̈c Le Marchand, Jeroen R. Huyghe, Niki Dimou, Mariana C. Stern, Stephanie A. Bien, Polly A. Newcomb, Anna Shcherbina, John D. Potter, Stephen B. Gruber, John L. Morrison
Bibliographic record
VenueUNC Libraries · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsnot available
FundersNational Cancer InstituteNational Heart, Lung, and Blood InstituteFaculty of Medicine and Health, University of SydneyWallenberg Centre for Molecular and Translational MedicineSchool of Public Health, Imperial College LondonNational Health and Medical Research CouncilCanadian Cancer Society Research InstituteJohns Hopkins Bloomberg School of Public HealthNational Institutes of HealthDeutschen Konsortium für Translationale KrebsforschungCanadian Institutes of Health ResearchTechnion-Israel Institute of TechnologyUniversitat de BarcelonaTokyo Medical and Dental UniversityDeutsches KrebsforschungszentrumClalit Health ServicesBinus UniversityMassey UniversityUmeå UniversitetHarvard T.H. Chan School of Public HealthKarolinska InstitutetMemorial University of NewfoundlandImperial College LondonUniversity of TorontoMinisterio de Economía y CompetitividadVetenskapsrådetNational Natural Science Foundation of ChinaMonash UniversityGénome QuébecMedical Center, University of PittsburghCity of HopeWorld Health OrganizationCedars-Sinai Medical CenterSchool of Public Health, University of MichiganSwedish Cancer FoundationAmerican Cancer SocietyUniversity of IoanninaKaiser Permanente Washington Health Research InstituteJohns Hopkins UniversityCentre International de Recherche sur le CancerCapital Medical UniversityDivision of Cancer Epidemiology and Genetics, National Cancer InstituteHuntsman Cancer InstituteUniversity of LeedsMcGill UniversityDivision of Cancer Prevention, National Cancer InstituteUniversity of PittsburghUniversity of WashingtonCenter for Gastrointestinal Biology and Disease, School of Medicine, University of North Carolina at Chapel HillUniversity of Texas MD Anderson Cancer CenterCenters for Disease Control and PreventionCancer Council VictoriaUniversity of MelbourneUniversity of North Carolina at Chapel HillHarvard UniversityBrigham and Women's HospitalNational Center for Advancing Translational SciencesKaiser PermanenteBroad InstituteWageningen University and ResearchCancer Research UKUniversity of Southern CaliforniaMassachusetts General HospitalU.S. Department of Health and Human Services
KeywordsColorectal cancerOncologyHormone therapyMedicineInternal medicineCancerGynecologyBreast cancer
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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.312
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) | 0.000 | 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 head0.003
GPT teacher head0.206
Teacher spread0.203 · 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 teacher head, not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Citations0
Published2024
Admission routes1
Has abstractno