Bibliographic record
Abstract
Birthweight is closely associated with morbidity and mortality of the newborn. Extensive research during the past 15 years has provided increasing evidence that birthweight is also important for health later in life. 1 Such information underscores the importance of birthweight monitoring. In this issue of the International Journal of Epidemiology Silva et al. publish a paper about birthweight fluctuations in Ribeirao Preto, Sao Paulo, Brazil. 2 During a 15-year period from 1978/79 to 1994 there was considerable economic development and a general improvement in education and income level accompanied by a population growth of 45% in the region. Even though the social indicators improved, a birthweight reduction of 122 g was observed. The downward trend may partly be explained by an increasing number of preterm births and factors related to marital status. A lesson from history Birthweight is a sensitive indicator of short-term changes in living conditions. Historical birthweight data has provided a new window to the living conditions of past populations. The current extensive socio-economic transformations in many parts of the developing world parallel the situation in Western Europe and North America during last part of the 1800s. Even though this period was characterized by general economic improvement with an overall increase in real income for the majority of the working classes, a corresponding downward trend in birthweight of approximately 200 g was observed in Vienna and Montreal. 3,4 Such periods of rapid socio-economic change may create a complex picture characterized by social injustice and instability with a more difficult situation for many childbearing women. In Ribeirao Preto the prevalence of single mothers doubled (from 6.8% to 12.2%) between the two periods studied by Silva et al. 2 and, even though the average income increased, the minimum wage was lower in 1994 than in 1978/79. 5
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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 | 0.011 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.010 | 0.003 |
| Research integrity | 0.054 | 0.061 |
| Insufficient payload (model declined to judge) | 0.009 | 0.010 |
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".