Maternal phenylketonuria: the importance of early control during pregnancy
Bibliographic record
Abstract
Commentary on the paper by Lee et al (see page 143) Drs Lee, Ridout, Walters, and Cockburn have reviewed data on 228 pregnancies occurring in women with phenylketonuria (PKU).1 This paper provides important data which support the main findings of the Collaborative Maternal PKU Study sponsored by the National Institute of Child Health and Human Development in Bethesda, Maryland, USA.2 Despite the fact that the data of Dr Lee et al are based on pregnancies occurring only in the United Kingdom, the findings verify two of the most important findings in our longitudinal, prospective study, which collected data from three different countries: the United States, Canada, and Germany. In any international study such as the latter, cultural and social differences can always interfere with statistical analyses. Therefore the fact that both studies support and concur that pregnancies in control by …
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.028 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".