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Record W2018573571 · doi:10.1002/mus.1108

Quadriceps muscle function and fatigue in women with Addison's disease

2001· article· en· W2018573571 on OpenAlexaff
Jennifer M. Jakobi, D.W. Killinger, Bernard M. Wolfe, Jeffrey L. Mahon, Charles L. Rice

Bibliographic record

VenueMuscle & Nerve · 2001
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsMedicineInternal medicineMuscle fatigueStimulationCardiologyAnesthesiaElectromyographyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

In nine patients with Addison's disease (mean +/- SE: 51 +/- 2 years) receiving conventional steroid treatment, and nine age-matched healthy controls (56 +/- 2 years), we investigated maximum voluntary quadriceps force (MVC) and contractile properties evoked with stimulation and central activation both at rest and during a submaximal intermittent fatigue task. The MVC was similar (-3%), but twitch tension (-27%) and central activation were significantly less (-7%), and tetanic half-relaxation time was approximately 40% slower in the patients. Twitch amplitudes were potentiated by 6% in the patients, but unchanged in the control group. The patients self-terminated a submaximal intermittent fatigue protocol (0.6 duty cycle) at approximately 5 +/- 1 min, whereas the controls stopped when they lost 50% of MVC force ( approximately 10 +/- 1 min). Force loss was similar between groups over the first 5 min of the fatigue task. In the patient group, maximal and submaximal relative integrated electromyogram (IEMG) increased significantly in the first minute of fatigue and remained elevated, whereas the controls exhibited a gradual increase in submaximal IEMG with little change in maximal IEMG. These results indicate that conventionally treated Addison's patients have similar MVC strength, but altered contractile properties and decreased endurance compared with controls.

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 score0.131
Threshold uncertainty score0.397

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 head0.021
GPT teacher head0.248
Teacher spread0.227 · 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

Citations22
Published2001
Admission routes1
Has abstractyes

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