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Record W2168412912 · doi:10.3389/fphys.2012.00491

Assessment of murine lung mechanics outcome measures: alignment with those made in asthmatics

2013· article· en· W2168412912 on OpenAlexafffund
Julia K. L. Walker, Monica Kraft, John T. Fisher

Bibliographic record

VenueFrontiers in Physiology · 2013
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood InstituteNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsAsthmaMedicineExacerbationLungRespiratory physiologyDiseaseIntensive care medicinePathogenesisLung diseaseImmunologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Although asthma is characterized as an inflammatory disease, recent reports highlight the importance of pulmonary physiology outcome measures to the clinical assessment of asthma control and risk of asthma exacerbation. Murine models of allergic inflammatory airway disease have been widely used to gain mechanistic insight into the pathogenesis of asthma; however, several aspects of murine models could benefit from improvement. This review focuses on aligning lung mechanics measures made in mice with those made in humans, with an eye toward improving the translational utility of these measures. A brief description of techniques available to measure murine lung mechanics is provided along with a methodological consideration of their utilization. How murine lung mechanics outcome measures relate to pulmonary physiology measures conducted in humans is discussed and we recommend that, like human studies, outcome measures be standardized for murine models of 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 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)0.017
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.288
Teacher spread0.273 · 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 designBench or experimental
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

Citations21
Published2013
Admission routes2
Has abstractyes

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