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Leisure time television watching, computer use and risks of breast, colorectal and prostate cancer: A Mendelian randomisation analysis
Nikos Papadimitriou, Nabila Kazmi, Niki Dimou, Konstantinos K. Tsilidis, Richard M. Martin, Sarah Lewis, Brigid M. Lynch, Michael Hoffmeister, Sun‐Seog Kweon, Li Li, Roger L. Milne, Lori C. Sakoda, Robert E. Schoen, Amanda I. Phipps, Jane C. Figueiredo, Ulrike Peters, Suzanne C. Dixon‐Suen, Marc J. Gunter, Neil Murphy
Bibliographic record
VenueCancer Medicine · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Human Genome Research InstituteMedicinska fakulteten, Umeå UniversitetInstituto de Salud Carlos IIIMedical Research CouncilCanadian Institutes of Health ResearchCenters for Disease Control and PreventionNational Institutes of HealthHellenic Health FoundationBiobanco VascoXunta de GaliciaInnovative Medicines InitiativeMutuelle Générale de l'Education NationaleDeutsche KrebshilfeNordForskVetenskapsrådetUniversity of PittsburghStockholms Läns LandstingHarvard T.H. Chan School of Public HealthCancer Research Foundation in Northern SwedenKarolinska InstitutetGeneralitat de CatalunyaCancerfondenNational Cancer InstituteFundación Científica Asociación Española Contra el CáncerCanadian Cancer Society Research InstituteMarshfield Clinic Research FoundationInstitut National de la Santé et de la Recherche MédicaleWorld Cancer Research FundKnut och Alice Wallenbergs StiftelseUniversity of BristolCentres de Recerca de CatalunyaUmeå UniversitetMinisterstvo Zdravotnictví Ceské RepublikyEuropean CommissionJunta de Castilla y LeónGray FoundationGénome QuébecOvarian Cancer Research FundBundesministerium für Bildung und ForschungUniversity of South FloridaSwedish Cancer FoundationAssociazione Italiana per la Ricerca sul CancroGenome CanadaInstitut Gustave-RoussyGrantová Agentura České RepublikyCentre International de Recherche sur le CancerLigue Contre le CancerDeutsches KrebsforschungszentrumGovernment of CanadaUniversity of CambridgeMcGill UniversityBreast Cancer Research FoundationVictorian Cancer AgencyFlorida Department of HealthPelotoniaMoffitt Cancer CenterAgència de Gestió d'Ajuts Universitaris i de RecercaNational Institute for Health and Care ResearchDivision of Cancer Prevention, National Cancer InstituteBrigham and Women's HospitalU.S. Department of Health and Human ServicesCancer Research UKXarxa de Bancs de Tumors de CatalunyaWorld Health OrganizationFondation du cancer du sein du QuébecMemorial Sloan-Kettering Cancer Center
KeywordsMedicineBreast cancerProstate cancerConfoundingColorectal cancerConfidence intervalOncologyInternal medicineEpidemiologyGynecologyDemographyCancer
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
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 score0.084
Threshold uncertainty score0.317
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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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
Citations3
Published2023
Admission routes1
Has abstractyes