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Record W4253379429 · doi:10.32920/ryerson.14645769.v1

Maternal sensitivity and infant stress system coordination and flexibility

2021· preprint· en· W4253379429 on OpenAlexaff
Brittany Jamieson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of GuelphToronto Metropolitan UniversitySystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsFlexibility (engineering)Maternal sensitivityDevelopmental psychologyPsychologySensitivity (control systems)

Abstract

fetched live from OpenAlex

Previous research has assessed the relationship between maternal sensitivity and infant hypothalamic-pituitary-adrenocortical [HPA] axis function, yet neglected additional stress systems. Using a multi-system method (HPA measured via cortisol and sympathetic nervous system via salivary alpha-amylase; sAA), we assessed the relationship between maternal sensitivity and infant stress system coordination and flexibility in response to acute stress. A community sample of 125 mother-infant dyads participated in a toy frustration (age 15 months) and separation procedure (age 16 months). Maternal sensitivity was measured via naturalistic observation. Multilevel-modeling analyses found that maternal sensitivity moderates the relationship between infant sAA and cortisol basal activity and reactivity, such that systems were coordinated at higher, but not lower, levels of sensitivity. SAA output was greater in response to separation compared to frustration, though sensitivity did not moderate this variability. Findings suggest that the quality of early caregiving relationships is important for the development of coordinated stress physiology.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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