Challenges in measuring changes in health and social indicators over time
Bibliographic record
Abstract
The paper by Mortensen et al 1 raises important questions in the study of time trends in fetal growth and other exposures and outcomes. Fetal growth is usually measured by birthweight for gestational age, and small for gestational age (SGA), typically defined using a percentile cut-off point of the weight for gestational age distribution, is a commonly used outcome in perinatal epidemiology studies.2 SGA is also considered an important risk factor3 4 in studies of perinatal exposures on child and adult outcomes, and therefore implicitly an important intermediate between prenatal exposures and morbidity and mortality. Defining SGA requires reference to a population standard to identify the percentiles. Ignoring the potential for bias that arises using a live birth standard,5 there are several choices of population standards that may have an effect on the study. The primary choice is whether to select an absolute or a relative reference. An absolute reference, where all births are compared with the same reference population (either internal or external), implies that SGA is a …
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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 | 0.147 | 0.429 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".