Additional file 1 of Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank
Bibliographic record
Abstract
Additional file 1: Supplement S1. Flowchart for inclusion and exclusion of participants. Supplement S2. Directed acyclic graph. Supplement S3. Covariates for Cox regression. Supplement S4. Missing information for covariates by fPC score quantiles. Supplement S5. Description of the physical activity patterns. Supplement S6. Correlation coefficients between fPCs and blood biomarkers. Supplement S7. Cox model results after exclusion of the first two years of follow-up. Supplement S8. Cox model results after restricting the analysis to never smokers. Supplement S9. Cox model results without adjustment for cardiometabolic disease status. Supplement S10. Cox model results with adjustment for shift work status. Supplement S11. Interaction terms for fPCs and covariates. Supplement S12. Sensitivity fPCA with different bandwidth estimations and kernel smoothers. Supplement S13. First four fPCs (A) and positive and negative scorers (B) when using an Epanechnikov kernel. Supplement S14. Correlation coefficients for fPCs and derived accelerometry.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.783 | 0.143 |
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.
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 source (direct Gemma or distilled Codex), not a consensus.
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".