MétaCan
Menu
Back to cohort
Record W4394224713 · doi:10.6084/m9.figshare.13466701

Additional file 1 of Adiposity, metabolites, and colorectal cancer risk: Mendelian randomization study

2020· dataset· en· W4394224713 on OpenAlexaff
Caroline J. Bull, Joshua A. Bell, Neil Murphy, Eleanor Sanderson, George Davey Smith, Nicholas J. Timpson, Barbara L. Banbury, Demetrius Albanes, Sonja I. Berndt, Stéphane Bezieau, D. Timothy Bishop, Hermann Brenner, Daniel D. Buchanan, Andrea N. Burnett‐Hartman, Graham Casey, Sergi Castellvı́-Bel, Andrew T. Chan, Jenny Chang‐Claude, Amanda J. Cross, Albert de la Chapelle, Jane C. Figueiredo, Steven Gallinger, Susan M. Gapstur, Graham G. Giles, Stephen B. Gruber, Andrea Gsur, Jochen Hampe, Heather Hampel, Tabitha A. Harrison, Michael Hoffmeister, Li Hsu, Wen‐Yi Huang, Jeroen R. Huyghe, Mark A. Jenkins, Corinne E. Joshu, Temitope O. Keku, Tilman Kühn, Sun‐Seog Kweon, Loı̈c Le Marchand, Christopher I. Li, Li Li, Annika Lindblom, Vicente Martín, Anne M. May, Roger L. Milne, Vı́ctor Moreno, Polly A. Newcomb, Kenneth Offit, Shuji Ogino, Amanda I. Phipps, Elizabeth A. Platz, John D. Potter, Conghui Qu, J. Ramón Quirós, Gad Rennert, Elio Ríboli, Lori C. Sakoda, Clemens Schafmayer, Robert E. Schoen, Martha L. Slattery, Catherine M. Tangen, Cornelia M. Ulrich, Fränzel J.B. van Duijnhoven, Bethany Van Guelpen, Kala Visvanathan, Pavel Vodička, Ludmila Vodičková, Hansong Wang, Emily White, Alicja Wolk, Michael O. Woods, Anna H. Wu, Peter T. Campbell, Wei Zheng, Ulrike Peters, Emma E. Vincent, Marc J. Gunter

Bibliographic record

VenueOpen MIND · 2020
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMemorial University of NewfoundlandUniversity of Toronto
Fundersnot available
KeywordsMendelian randomizationColorectal cancerGeneticsBiologyInternal medicineBioinformaticsMedicineCancerGeneGenotypeGenetic variants

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. Genetic variants used to instrument BMI, WHR and metabolites. Table S2. Assesment of instrument strength. Table S3. Colorectal cancer case distributions by study, sex and site. Table S4. LogOR colorectal cancer per SD higher BMI or WHR. Table S5. Beta change in NMR-detected metabolite per SD higher BMI or WHR. Table S6. LogOR colorectal cancer per SD higher BMI or WHR-driven NMR-detected metabolite. Table S7. Risk of overall colorectal cancer per SD higher adipose or metabolite trait, estimated using multivariable Mendelian randomization. Table S8. Posthoc investigations.

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)0.002
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.457
Threshold uncertainty score0.775

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.4570.066

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicCancer, Lipids, and MetabolismFrench-language works237,207