Environmental and reproductive health: A spatial analysis of adverse birth outcomes and environmental contaminants in British Columbia.
Bibliographic record
Abstract
Exposure to contaminants during pregnancy is associated with certain adverse birth outcomes that require further investigation. Community reproductive and environmental health risk maps were produced utilizing birth data obtained from the B.C. Perinatal Health Program and environmental contaminant data from the National Pollutant Release inventory and other national and provincial sources. Geographical information systems (GIS) were utilized to spatially relate perinatal and environmental hazard data, and the risk of adverse birth outcomes was tested using watersheds as the ecological aggregation unit adjusting for individual-level risk factors. The perinatal data included birth outcomes (low birth weight, prematurity, inter-uterine growth restriction, congenital anomalies, stillbirths) and numerous maternal and antenatal risk factor data for all singleton births in B.C. from 2001 to 2006. Small but significant increased risks of adverse birth outcomes were found in high and intermediate hazard watersheds compared to low hazard watersheds. This suggests a possible environmental effect on these reproductive outcomes, however, further studies are needed to corroborate these results. --P.ii.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".