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Record W2147290138 · doi:10.1186/1710-1492-4-1-29

Stress and Childhood Asthma Risk: Overlapping Evidence from Animal Studies and Epidemiologic Research

2008· article· en· W2147290138 on OpenAlexvenueno aff
Rosalind J. Wright

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
Fundersnot available
KeywordsAsthmaImmune systemPrenatal stressAllergyImmunologyMedicineDevelopmental psychologyPsychologyNeurosciencePregnancyBiologyGeneticsOffspring

Abstract

fetched live from OpenAlex

: Rapidly expanding evidence increasingly strengthens the evidence linking psychological factors to asthma and allergy expression. Parallel studies in animals and humans demonstrating the influence of prenatal maternal stress and early caregiving experiences on the disrupted regulation of defensive biological systems [eg, sympathetic and adrenomedullary (SAM) system and the hypothalamicpituitary-adrenocortical (HPA) axis] provide strong proof of concept for this line of research. The consequent altered neuroimmune responses may influence the expression of immune-mediated disorders such as asthma as well as enhance an individual's susceptibility to other environmental factors that may also contribute to asthma risk.

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)0.005
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.207
GPT teacher head0.426
Teacher spread0.219 · 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

Citations28
Published2008
Admission routes1
Has abstractyes

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