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Record W2799276341 · doi:10.1182/blood-2017-11-814608

Association of polygenic risk score with the risk of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis

2018· article· en· W2799276341 on OpenAlexaff
Geffen Kleinstern, Nicola J. Camp, Lynn R. Goldin, Celine M. Vachon, Claire M. Vajdic, Sílvia de Sanjosé, J. Brice Weinberg, Yolanda Benavente, Delphine Casabonne, Mark Liebow, Alexandra Nieters, Henrik Hjalgrim, Mads Melbye, Bengt Glimelius, Hans‐Olov Adami, Paolo Boffetta, Paul Brennan, Marc Maynadié, James McKay, Pier Luigi Cocco, Tait D. Shanafelt, Timothy G. Call, Aaron D. Norman, Curtis A. Hanson, Dennis P. Robinson, Kari G. Chaffee, Angela Brooks‐Wilson, Alain Monnereau, Jacqueline Clavel, Martha Glenn, Karen Curtin, Lucía Conde, Paige M. Bracci, Lindsay M. Morton, Wendy Cozen, Richard K. Severson, Stephen J. Chanock, John J. Spinelli, James B. Johnston, Nathaniel Rothman, Christine F. Skibola, José F. Leis, Neil E. Kay, Karin E. Smedby, Sonja I. Berndt, James R. Cerhan, Neil E. Caporaso, Susan L. Slager

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityCancerCare ManitobaBC Cancer Agency
FundersNational Cancer InstituteNational Center for Advancing Translational SciencesNational Center for Chronic Disease Prevention and Health PromotionWorld Health Organization
KeywordsLymphocytosisChronic lymphocytic leukemiaMedicineInternal medicineLeukemiaOncologyImmunology

Abstract

fetched live from OpenAlex

). In conclusion, our validated PRS was strongly associated with CLL risk, adding information beyond FH. The PRS provides a means of identifying those individuals at greater risk for CLL as well as those at increased risk of MBL, a condition that has potential clinical impact beyond CLL.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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)0.001
metaresearch head score (Gemma)0.005
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine 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

Citations32
Published2018
Admission routes1
Has abstractyes

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