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Record W2785936896 · doi:10.1055/s-0037-1606219

Environmental Causes of Asthma

2018· review· en· W2785936896 on OpenAlexaff
D W Cockcroft

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineAsthmaBronchoconstrictionImmunologyPathophysiology of asthmaAllergenInflammationAllergyImmunoglobulin EByssinosisAirwayEnvironmental healthAntibodyAnesthesia

Abstract

fetched live from OpenAlex

Environmental factors which cause asthma are those that induce airway inflammation with eosinophils (more common) or neutrophils along with airway hyperresponsiveness (AHR). The most common of these (indeed the most common cause of asthma) are IgE-mediated inhalant allergen exposures. Allergen-induced AHR and inflammation are both associated with the allergen-induced late asthmatic response (LAR). Although allergens were previously recognized only as causes of symptoms and bronchoconstriction in asthmatics, we now appreciate them as causes of the fundamental pathophysiologic features of asthma. Low-molecular-weight chemical sensitizers, causes of occupational asthma, also cause asthma in a manner analogous to allergen. Acute irritant-induced asthma (reactive airways dysfunction syndrome) following a very heavy irritant exposure and chronic irritant-induced asthma following repeated high exposures can also induce persistent or permanent changes (inflammation and AHR) consistent with asthma. Textile dust exposure produces a different form of airway disease (byssinosis) which is less frequently observed currently. Environmental exposure to tobacco smoke facilitates the development of asthma in children. Personal smoking and environmental air pollution have an inconsistent and likely generally small effect in causing asthma.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.043
GPT teacher head0.376
Teacher spread0.333 · 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 designOther design
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

Citations38
Published2018
Admission routes1
Has abstractyes

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