Additional file 1 of Variability in newborn telomere length is explained by inheritance and intrauterine environment
Bibliographic record
Abstract
Additional file 1: Figure S1. DNA quality analysis by agarose gel electrophoresis. Figure S2. Flowchart of sample selection and analysis steps. Figure S3. Trans-ethnic genome-wide association studies on telomere length. Figure S4. Boxplots of the top six genetic variants. Figure S5. Effect allele frequencies of the top six genetic variants. Figure S6. Heat map of pairwise Pearson correlation coefficients between clinical variables. Figure S7. Significant sex-specific effects of the selected factors on newborn telomere length. Figure S8. Association between maternal telomere length and antenatal maternal factors. Figure S9. The variance percentage explained by each factor. Figure S10. Scatter plot of average relative telomere length of cord blood and cord tissue. Figure S11. Mediation analysis of maternal telomere length. Table S1. Intra-class correlation coefficient of intra-assay and inter-assay for telomere length measurements. Table S2. Comparison of the basic characteristics of 950 subjects and the full cohort. Table S3. Clinical characteristics of maternal-offspring subjects in this study and linear regression results for newborn TL. Table S4. The association of SNPs at 3q26.2 in the GWAS results of newborn and maternal telomere lengths and the meta-analysis results. Table S5. Pairwise Linkage Disequilibrium measures between the top six genetic variants. Table S6. Linear regression results between maternal telomere length and antenatal maternal factors. Table S7. The results of sensitivity analysis after adding DNA storage time and sample collection month in the best multivariate models of newborn telomere length. Table S8. The results of sensitivity analysis after further adjustment for DNA storage time and sample collection month in the association studies between maternal telomere length and antenatal maternal factors. Table S9. The genetic variants in a strong Linkage Disequilibrium with rs10936600. Table S10. The association of candidate genes in the GWAS results of newborn and maternal telomere lengths and the meta-analysis results.
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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 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.885 | 0.113 |
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".