Birth weight and catch up growth are associated with childhood impulsivity in two independent cohorts
Bibliographic record
Abstract
Individuals born after intrauterine growth restriction (IUGR) are more impulsive towards palatable foods, but it is not clear 1) if IUGR-related impulsivity is specific for foods and solely based on response inhibition and 2) if the development of impulsivity is due to being born IUGR per se or to growing up fast in the first few years of life (catch up growth). Children were classified in the IUGR group if the birth weight ratio was below 0.85. Delta z score for BMI was used as a measure of catch up growth. In MAVAN (N = 274), impulsivity was measured by the Information Sampling Task from the Cambridge Neuropsychological Test Automated Battery (IST - CANTAB), and in GUSTO using the Sticker Delay Task (N = 327). There is a significant effect of interaction between being born IUGR and the magnitude of catch up growth on the reflection impulsivity from IST-CANTAB at 60 months, in which greater catch up growth associates with greater impulsivity in the IST fixed condition in IUGR children. The finding was reproduced in children from the GUSTO cohort using the Sticker Delay Task. We confirmed that catch up growth interacts with IUGR, having a major role in the development of impulsivity in the first years of life and influencing inhibitory control and decision making processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".