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Record W2000258320 · doi:10.1097/aci.0000000000000101

The evolution of the hygiene hypothesis

2014· review· en· W2000258320 on OpenAlexaff
Denise Daley

Bibliographic record

VenueCurrent Opinion in Allergy and Clinical Immunology · 2014
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMicrobiomeHygiene hypothesisAsthmaWheezeRhinovirusMedicineImmunologyHuman microbiomeImmune systemBioinformaticsBiologyVirus

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Understanding the mechanisms involved in the development of asthma and allergic diseases is expanding, due in part to sequencing advances that have led to the identification of new viral strains such as human rhinovirus strain C (HRV-C) and the human microbiome project. RECENT FINDINGS: Recent studies have identified new ways in which viral and microbial exposures in early life interact with host genetic background/variants to modify the risk for developing asthma and allergic diseases. Recent research suggests that HRV-C is the main pathogenic agent associated with infant wheeze, hospitalizations and likely the subsequent development of asthma. Pulmonary He MRI suggests that HRV infection in early childhood and subsequent immune responses initiate airway remodeling. Numerous studies of the microbiome indicate that intestinal and airway microbiome diversity and composition contribute to the cause of asthma and allergic diseases. SUMMARY: Susceptibility to asthma and allergic diseases is complex and involves genetic variants and environmental exposures (bacteria, viruses, smoking, and pet ownership), alteration of our microbiome and potentially large-scale manipulation of the environment over the past century.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.003

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 head0.097
GPT teacher head0.414
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2014
Admission routes1
Has abstractyes

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