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Record W2887403611 · doi:10.1002/cpmo.49

Critical Assessment of the <i>mdx</i> Mouse with <i>Ex Vivo</i> Eccentric Contraction of the Diaphragm Muscle

2018· article· en· W2887403611 on OpenAlexafffund
Gregory C. Addicks, Phillip Marshall, Bernard J. Jasmin, Jean‐Marc Renaud, Hongbo Zhang, Keir J. Menzies

Bibliographic record

VenueCurrent Protocols in Mouse Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaOntario Institute for Regenerative MedicineNatural Science Foundation of Guangdong ProvinceCanadian Institutes of Health ResearchSun Yat-sen UniversityUniversity of Ottawa
KeywordsEccentricEx vivoDiaphragm muscleContraction (grammar)Muscle contractionAnatomyDiaphragm (acoustics)In vivoMedicineInternal medicineBiologyRespiratory systemPhysicsStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Muscle function and health progressively deteriorate during the progression of muscle dystrophies. The ability to objectively characterize muscle function and muscle damage is useful not only when comparing variants of dystrophy models, but also for characterizing the effects of interventions aiming to improve or halt the progressive decline of muscle function and muscle health. The protocols in this chapter describe the use of ex vivo eccentric contraction of the diaphragm muscle as a measure of muscle susceptibility to damage. Because muscle has a robust regenerative capacity, unhealthy muscle may be functionally close to normal; therefore, protocols for ex vivo characterization of muscle are often essential for assessing the effects of interventions. Additional methods that can be applied for assessment of dystrophic muscle are also highlighted. © 2018 by John Wiley & Sons, Inc.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.391

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 studies0.0000.001
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 head0.017
GPT teacher head0.349
Teacher spread0.332 · 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 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

Citations2
Published2018
Admission routes2
Has abstractyes

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