Bibliographic record
Abstract
To the Editor. — Fewtrell et al1 raise interesting questions about supplementation of preterm infant formula with docosahexaenoic acid (DHA) and arachidonic acid (AA). In this short-term study—about a month during initial hospitalization—feeding premature formula with added egg lipid (a source of DHA and AA) and evening primrose oil (source of γ-linolenic acid) did not provide a significant advantage in neurodevelopment at 9 or 18 months’ corrected age (CA) and appeared to negatively impact growth. These results are in stark contrast to results of several large studies in which no negative effects on growth and development or increase in adverse events2–7 were reported. Some studies, in fact, found significant benefits in growth5,6 and/or neurodevelopment.4,6 It is important to provide an additional perspective on the differences between these studies that may help explain the disparate results, particularly to prevent undue alarm, as premature infant formulas with added long-chain polyunsaturated fatty acids (LCPUFAs) have been available commercially in many countries for a number of years and are just now becoming available in North America. First, although Fewtrell et al1 did not find statistically significant effects of LCPUFA supplementation on neurodevelopment, the authors point out that there was a small advantage in favor of the supplementation (+2.6 points on the Bayley Mental Development Index [MDI] and +2 points on the Bayley Psychomotor Development Index [PDI]) at 18 months’ CA, with greater yet statistically insignificant improvements for those infants <30 weeks’ gestational age. The authors comment that a much larger study, estimated at 256 infants per group, would be required to confirm a benefit of 2.6 points for the Bayley MDI in the overall population studied, or 60 to 70 infants <30 weeks’ gestational age to confirm a significant difference in this population. …
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.022 | 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".