Additional file 1 of Associations of overweight and gestational diabetes mellitus with free sugars from solid and liquid sources: cross-sectional and nested case-control analyses
Bibliographic record
Abstract
Additional file 1: Supplemental Table 1. ICD-10 Diagnostic Codes Used to Identify Outcomes from the National 2004–2017 Discharge Abstract Database. Supplemental Table 2. Comparison between participants who had completed both 1st and 2nd 24-h dietary recalls. Supplemental Table 3. Secondary analysis: Multivariate associations between solid and liquid sources of free sugars with overweight and with GDM case status when adjusting for mutually exclusive categories of free sugar intake. Supplemental Table 4. Sensitivity analysis: Multivariate associations between solid and liquids sources of free sugars with overweight and with GDM case status without adjustment for total energy intake. Supplemental Table 5. Multivariate associations between baseline characteristics with overweight and with GDM case status. Supplemental Figure 1. Percent of all participants above various thresholds of free sugar (FS) intake as a percent of total energy (TE%)1. Supplemental Figure 2. Percent of delivery cohort above various thresholds of free sugar (FS) intake as a percent of total energy (TE%)1. Supplemental Figure 3. Top sources of free sugars from solid sources. Supplemental Figure 4. Top sources of free sugars from liquid sources.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.666 | 0.041 |
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".