Incidence of low birth weight in Mexico: A descriptive retrospective study from 2008–2017
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
According to the WHO, low birth weight (LBW) affects 15-20% of newborns worldwide. In Mexico, there are no national, state, nor municipal estimates that inform the country's situation over time. The purpose of this study was to estimate the incidence of LBW at the national, state, and municipal levels from 2008 to 2017, and to estimate the LBW incidence based on maternal sociodemographic characteristics, prenatal care and marginalization indexes at the national level using open national data. We used spatial data analysis to georeferenced LBW incidence at the three levels of geographical disaggregation studied. At the national level, the incidence of LBW increased progressively from 6.2% (2008) to 7.1% (2017), and the country's capital represented the area with the highest incidence. Southeastern and central states reported the highest LBW regional incidence. At the municipal level, the number of municipalities with an incidence of LBW ≥8% increased in both male and female newborns. The incidence of LBW was higher as the marginalization indexes increases. The results from this study may assist in the identification of vulnerable groups and the development of public health programs and policies with an intersectoral approach that improves maternal and child nutrition.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it