Sensitivity to facial expressions among extremely low birth weight survivors in their 30s
Bibliographic record
Abstract
The current study investigated the impact of birth weight on the ability to recognize facial expressions in adulthood among the longest known prospectively followed cohort of extremely low birth weight survivors (ELBW; <1,000 g). We measured perceptual threshold to detect subtle facial expressions and confusion among different emotion categories in order to disentangle visual perceptual ability from emotional processing. ELBW adults (N = 64, Mage = 31.9 years) were more likely than normal birth weight (NBW) controls (N = 82, Mage = 32.5 years) to see fear in angry faces. This finding was not a result of increased perceptual efficiency in processing fearful expressions in the ELBW adults, since the two groups did not differ on their threshold to detect emotion in low intensity facial expressions. These findings suggest that a processing bias toward fear may reflect long‐term developmental effects from being born at ELBW that may portend socioemotional problems that characterize ELBW survivors.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".