Where and to What Extent is Prevention of Low Birth Weight Possible?
Bibliographic record
Abstract
Law birth weight (LBW), due to shortened gestation and/or inadequate fetal growth. is the major determinant of infant mortality and morbidity. Despite improvements in infant mortality, them has been no reduction in LBW rates. The authors examined the relationship between 33 maternal characteristics and the increased risks of preterm (PT) delivery or small-for-gestational-age (SGA) births in 76,444 Alberta women 1994-1997. PT was associated with preexisting medical conditions, obstetrical history, and pregnancy complications. Modifiable factors such as advanced maternal age contributed only 11% to the overall PT risk. SGA births were associated with several modifiable factors, including low prepregnancy weight, maternal age, smoking, drinking, and drug dependency. These contributed to 29% and 31% of PTand term SGA births. Smoking remains an important target for intervention, having contributed to 8% of PT births and about 24% of SGA births. SGA appears to be more amenable to prevention than PT delivery.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".