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Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes
Sonja I. Berndt, Joseph Vijai, Yolanda Benavente, Nicola J. Camp, Alexandra Nieters, Zhaoming Wang, Karin E. Smedby, Geffen Kleinstern, Henrik Hjalgrim, Caroline Besson, Christine F. Skibola, Lindsay M. Morton, Angela Brooks‐Wilson, Lauren R. Teras, Charles E. Breeze, Joshua Arias, Hans‐Olov Adami, Demetrius Albanes, Kenneth C. Anderson, Stephen M. Ansell, Bryan A. Bassig, Nikolaus Becker, Parveen Bhatti, Brenda M. Birmann, Paolo Boffetta, Paige M. Bracci, Paul Brennan, Elizabeth E. Brown, Laurie Burdett, Lisa Cannon‐Albright, Ellen T. Chang, Brian C.‐H. Chiu, Charles C. Chung, Jacqueline Clavel, Pierluigi Cocco, Graham A. Colditz, Lucía Conde, David V. Conti, David G. Cox, Karen Curtin, Delphine Casabonne, Immaculata De Vivo, Arjan Diepstra, W. Ryan Diver, Ahmet Doǧan, Christopher K. Edlund, Lenka Foretová, Joseph F. Fraumeni, Attilio Gabbas, Hervé Ghesquières, Graham G. Giles, Sally L. Glaser, Martha Glenn, Bengt Glimelius, Jian Gu, Thomas M. Habermann, Christopher A. Haiman, Corinne Haïoun, Jonathan N. Hofmann, Theodore R. Holford, Elizabeth A. Holly, Amy Hutchinson, Aalin Izhar, Rebecca D. Jackson, Ruth F. Jarrett, Rudolph Kaaks, Eleanor Kane, Laurence N. Kolonel, Yinfei Kong, Peter Kraft, Anne Kricker, Annette Lake, Qing Lan, Charles Lawrence, Dalin Li, Mark Liebow, Brian K. Link, Corrado Magnani, Marc Maynadié, James McKay, Mads Melbye, Lucia Miligi, Roger L. Milne, Thierry Jo Molina, Alain Monnereau, Rebecca Montalvan, Kari E. North, Anne J. Novak, Kenan Onel, Mark P. Purdue, Kristin A. Rand, Elio Ríboli, Jacques Riby, Eve Roman, Gilles Salles, Douglas W. Sborov, Richard K. Severson, Tait D. Shanafelt, Martyn T. Smith, Alexandra Smith, Kevin Song, Lei Song, Melissa C. Southey, John J. Spinelli, Anthony Staines, Deborah M. Stephens, Heather J. Sutherland, Kaitlyn Tkachuk, Carrie A. Thompson, Hervé Tilly, Lesley F. Tinker, Ruth C. Travis, Jennifer Turner, Celine M. Vachon, Claire M. Vajdic, Anke van den Berg, David J. Van Den Berg, Roel Vermeulen, P. Vineis, Sophia S. Wang, Elisabete Weiderpass, George J. Weiner, Stephanie J. Weinstein, Nicole Wong Doo, Yuanqing Ye, Meredith Yeager, Kai Yu, Anne Zeleniuch‐Jacquotte, Yawei Zhang, Tongzhang Zheng, Elad Ziv, Joshua Sampson, Nilanjan Chatterjee, Kenneth Offit, Wendy Cozen, Xifeng Wu, James R. Cerhan, Stephen J. Chanock, Susan L. Slager, Nathaniel Rothman
Bibliographic record
VenueLeukemia · 2022
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityBC Cancer Agency
FundersCilagDivision of Cancer Epidemiology and Genetics, National Cancer InstituteMedical Research CouncilCelgeneJanssen PharmaceuticalsGilead SciencesServierAmgenPfizerGlaxoSmithKlineWorld Health OrganizationNational Cancer InstituteNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsGenome-wide association studyBiologyHeritabilityGeneticsGenetic associationGenetic architectureGermlineMissing heritability problemLocus (genetics)Quantitative trait locusSingle-nucleotide polymorphismGeneGenotype
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.800
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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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 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
Citations32
Published2022
Admission routes1
Has abstractno