Additional file 1 of Impact of air pollution on stunting among children in Africa
Bibliographic record
Abstract
Additional file 1: Table S1. Study sample with filtered observations by country. Table S2. Associations (95% Confidence Intervals) between in-utero PM2.5 and HAZ, and the Odds Ratios (95% Confidence Intervals) corresponding to associations between in-utero PM2.5 exposure and stunting for an increase of 10 μg/m3 in PM2.5. Standard errors presented are clustered at the cluster-level. Table S3. Associations (95% Confidence Intervals) between in-utero PM2.5 and HAZ, and the Odds Ratios (95% Confidence Intervals) corresponding to associations between in-utero PM2.5 and stunting for an increase of 10 μg/m3 in PM2.5. Standard errors presented are clustered at the cluster-level. Note that sample sizes vary across Models because some fixed effects categories lack within-category variation in the independent variable (resulting in that category being dropped). The main model is highlighted. Table S4. Associations (95% Confidence Intervals) between in-utero and early-life PM2.5 and HAZ, and the Odds Ratios (95% Confidence Intervals) corresponding to associations between in-utero and early-life PM2.5 and stunting for an increase of 10 μg/m3 in PM2.5. Standard errors presented are clustered at the cluster-level. Note that sample sizes vary across Models because some fixed effects categories lack within-category variation in the independent variable (resulting in that category being dropped). . The main model is highlighted. Table S5. Associations (95% Confidence Intervals) between early-life PM2.5 and HAZ, and the Odds Ratios (95% Confidence Intervals) corresponding to associations between early-life PM2.5 and stunting for an increase of 10 μg/m3 in PM2.5. Standard errors presented are clustered at the cluster-level. Note that sample sizes vary across Models because some fixed effects categories lack within-category variation in the independent variable (resulting in that category being dropped). . The main model is highlighted. Table S6. Associations (95% Confidence Intervals) between in-utero PM2.5 and HAZ, and the Odds Ratios (95% Confidence Intervals) corresponding to associations between in-utero PM2.5 and stunting for an increase of 10 μg/m3 in PM2.5 derived from fully-adjusted models (Model 6 in Table S3), using household-fixed effects instead of cluster-specific fixed effects. Table S7. Associations (95% Confidence Intervals) between in-utero and early-life PM2.5 and HAZ, and stunting for an increase of 10 μg/m3 in PM2.5 derived from fully-adjusted models (Model 6 in Table S4), using household-fixed effects instead of cluster-specific fixed effects.
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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 | 0.001 | 0.021 |
| 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 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.766 | 0.069 |
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".