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Record W2041812239 · doi:10.1155/2013/203061

Linking Early Adversity, Emotion Dysregulation, and Psychopathology: The Case of Extremely Low Birth Weight Infants

2013· article· en· W2041812239 on OpenAlexaff
Lauren Drvaric, Ryan J. Van Lieshout, Louis A. Schmidt

Bibliographic record

VenueChild Development Research · 2013
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychopathologyPsychologyVagal toneDevelopmental psychologyPopulationLow birth weightElectroencephalographyClinical psychologyNeuroscienceAutonomic nervous systemHeart rateMedicineInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.305
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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