Additional file 1 of Late preterm birth and growth trajectories during childhood: a linked retrospective cohort study
Bibliographic record
Abstract
Additional file 1: Supplemental Table 1. Data sources used to define study participant characteristics and variable operationalization. Supplemental Table 2. Model fit comparison of predicted values at specific time points for the outcome of weight trajectory between the original model (3 knot) and model with the best fit (4 knot). Supplemental Table 3. Model fit comparison of predicted values at specific time points for the outcome of height trajectory between the original model (3 knot) and model with the best fit (4 knot). Supplemental Table 4. Predicted mean weight (kg) and 95% CI at each age (knot point) by gestational age category. Supplemental Table 5. Predicted mean height (cm) and 95% CI at each age (knot point) by gestational age category. Supplemental Table 6. Mean differences in monthly growth rates for zweight, zheight, and zBMI by gestational age categories during each growth period for study participants (N=4423). Supplemental Figure 1. Flowchart of study participants with weight/height data. Supplemental Figure 2. Growth curves for World Health Organization (WHO) standardized weight trajectories from 0 to 150 months by gestational age categories. The lines represent the growth curve, and the shaded areas represent the 95% confidence intervals. Supplemental Figure 3. Growth curves for World Health Organization (WHO) standardized height trajectories from 0 to 150 months by gestational age categories. The lines represent the growth curve, and the shaded areas represent the 95% confidence intervals. Supplemental Figure 4. Growth curves for World Health Organization (WHO) standardized BMI trajectories from 0 to 150 months by gestational age categories. The lines represent the growth curve, and the shaded areas represent the 95% confidence intervals.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.490 | 0.032 |
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".