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Record W2611251974 · doi:10.1111/bjh.14702

Physical activity, obesity and survival in diffuse large B‐cell and follicular lymphoma cases

2017· article· en· W2611251974 on OpenAlexafffund
Terry Boyle, Joseph M. Connors, Randy D. Gascoyne, Brian Berry, Laurie H. Sehn, Morteza Bashash, John J. Spinelli

Bibliographic record

VenueBritish Journal of Haematology · 2017
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaRoyal Jubilee HospitalPublic Health OntarioUniversity of TorontoBC Cancer Agency
FundersNational Cancer InstituteBC Cancer AgencyNational Health and Medical Research CouncilCanadian Institutes of Health ResearchKillam TrustsMichael Smith Health Research BC
KeywordsFollicular lymphomaMedicineLymphomaHazard ratioInternal medicineDiffuse large B-cell lymphomaBody mass indexConfidence intervalInternational Prognostic IndexNon-Hodgkin's lymphomaOncologyObesityProportional hazards modelGastroenterology

Abstract

fetched live from OpenAlex

There is limited information concerning the impact of physical activity and obesity on non-Hodgkin lymphoma (NHL) prognosis. We examined the associations between pre-diagnosis physical activity and body mass index (BMI) with survival in 238 diffuse large B-cell (DLBCL) and 175 follicular lymphoma cases, with follow-up from 2000 to 2015. The most physically active DLBCL cases had 41% lower risk of dying in the follow-up period than the least active [Hazard ratio (HR) = 0·59, 95% confidence interval (CI) = 0·36-0·96], while obese follicular lymphoma cases had a 2·5-fold risk of dying (HR = 2·52, 95% CI = 1·27-5·00) compared with cases with normal BMI. NHL-specific survival results were similar.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.286
Teacher spread0.269 · 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

Citations25
Published2017
Admission routes2
Has abstractyes

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