The influence of the built environment on adverse birth outcomes
Bibliographic record
Abstract
Adverse birth outcomes are associated with neonatal morbidity and mortality, and higher risk for coronary heart disease, non-insulin-dependent diabetes and hypertension in adulthood. Although there has been considerable research investigating the association between maternal and environmental factors on adverse birth outcomes, one risk factor, not fully understood, is the influence of the built environment. A search of MEDLINE, Scopus, and Cochrane was conducted to find articles assessing the influence of the built environment on preterm birth (PTB), low birth weight (LBW), and small-for-gestational-age (SGA). In total, 41 studies met our inclusion criteria, and were organized into nine categories: Roadways, Greenness, Power Plants, Gas Stations/Wells, Waste Management, Power Lines, Neighborhood Conditions, Food Environment, and Industry. The most common built environmental variable was roads/traffic, encompassing 17/41 (41%) of the articles reviewed, of which 12/17 (71%) found a significant small to moderate association between high traffic exposure and adverse birth outcomes.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".