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Insights into asthmatic airway remodelling through murine models

2011· review· en· W1881976994 on OpenAlex
Saba Al Heialy, Toby K. McGovern, James G. Martin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRespirology · 2011
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcGill UniversityChristie (Canada)
FundersCanadian Institutes of Health Research
KeywordsMedicineImmunologyAirwayAsthmaVascular remodelling in the embryoInfiltration (HVAC)Pathology

Abstract

fetched live from OpenAlex

Asthma is a chronic disorder of the airways associated in many instances with structural changes of the airways, termed airway remodelling. Irritant and allergen-induced murine models have been used to further understand the mechanisms of airway remodelling. The infiltration of the airways by inflammatory cells, such as T lymphocytes, mast cells, eosinophils, neutrophils and macrophages after repeated allergen challenges may be important effectors in the initiation and perpetuation of airway remodelling through the release of inflammatory mediators and growth factors. Interleukins-4 and -13 have been widely studied in experimental models, and have been shown to play a significant role in airway remodelling. Recently, a role for Th17 cells has been established. Other mediators involved in this process are ligands of the epidermal growth factor receptor, matrix metalloproteases and cysteinyl leukotrienes. A better understanding of the mechanisms leading to airway remodelling in allergic diseases may lead to the identification of novel therapeutic strategies but validation in human subjects is required for potential targets.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.089
GPT teacher head0.344
Teacher spread0.256 · 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