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Record W3099743922 · doi:10.31542/muse.v4i1.1245

Are we too clean? A History and Analysis of the Hygiene Hypothesis

2020· article· en· W3099743922 on OpenAlexaffvenue
Riley Joel Steed

Bibliographic record

VenueMacEwan University Student eJournal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMacEwan University
Fundersnot available
KeywordsHygiene hypothesisAtopyDiseaseHygieneAllergyImmunologyMedicinePsychologyPathology

Abstract

fetched live from OpenAlex

Since the second half of the 20th century, the incidence of atopic disease has been on the rise. Allergies and rhinitis have become so common that some have called it an epidemic (Strachan, 1989). Initial research into the reasons for the rapid increase was done by David P Strachan, and he proposed the “hygiene hypothesis,” a theory claiming that early childhood infections can protect us against atopic diseases later in life (Strachan, 1989). Subsequent research found an interaction between T-helper 1 and T-helper 2 cells that, for many years, was considered to be the mechanism by which the hygiene hypothesis functioned (Romagnani, 1992). Eventually, it was discovered that this interaction did not work exactly as previously thought, and Graham A. Rook introduced a new theory to match the more recent research. Rook proposed the “old friends” hypothesis, which suggested that certain microbes, which evolved alongside humans, were responsible for protecting us against atopic disease (Rook et al., 2004). According to Rook, modern lifestyles have eliminated many of those microbes from our normal flora, and that explains the recent rise in atopic disease (Rook et al., 2004). The “old friends” hypothesis is now the prevalent atopic disease theory in epidemiology, and has helped improve both public and scientific understanding of the relationship between infection, hygiene, and atopy (Stiesma, et al., 2015).

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)0.000
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 score0.287
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.026
GPT teacher head0.226
Teacher spread0.200 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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