Linking Early Adversity, Emotion Dysregulation, and Psychopathology: The Case of Extremely Low Birth Weight Infants
Bibliographic record
Abstract
The ability to regulate emotion is a crucial process that humans utilize in order to adapt to the demands of environmental constraints. Individuals exposed to early adverse life events such as being born at an extremely low birth weight (ELBW, 501–1000 g) are known to have problems regulating emotion which have been linked to the development of psychopathology in this population. Recent studies have used psychophysiological measures, such as electroencephalogram (EEG) and cardiac vagal tone, to index emotion regulatory processes. The purpose of this paper was three-fold: (1) to investigate the relation between ELBW and emotion regulation issues (pathway 1), (2) to review studies investigating the relation between early emotion regulation and later internalizing problems (pathway 2); and (3) to provide a model in which two psychophysiological measures (i.e., frontal EEG asymmetry and cardiac vagal tone) are suggested to understand the proposed conceptual pathways in the relation between ELBW and psychopathology.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".