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Insights into muscle diseases gained by phosphorus magnetic resonance spectroscopy

2000· review· en· W2084576650 on OpenAlexaff
Zohar Argov, Mervi L�fberg, Douglas L. Arnold

Bibliographic record

VenueMuscle & Nerve · 2000
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsFibromyalgiaMetabolic diseaseMitochondrial myopathyMuscle diseaseMedicineMagnetic resonance imagingEndocrine systemDiseaseInternal medicineEndocrinologyPathologyNuclear magnetic resonanceChemistryBiochemistryRadiologyPhysicsMitochondrial DNA

Abstract

fetched live from OpenAlex

Phosphorus magnetic resonance spectroscopy (P-MRS) has now been used in the investigation of muscle energy metabolism in health and disease for over 15 years. The present review describes the basics of the metabolic observations made by P-MRS including the assumptions and problems associated with the use of this technique. Extramuscular factors, which may affect the P-MRS results, are detailed. The important P-MRS observations in patients with mitochondrial myopathies, including the monitoring of experimental therapies, are emphasized. The findings in other metabolic myopathies (those associated with glycolytic defects or endocrine disturbances) and in the destructive myopathies (the dystrophies and the inflammatory myopathies) are also described. Observations made in normal and abnormal fatigue, fibromyalgia, and malignant hyperthermia are considered. Finally, a summary of the possible diagnostic use of P-MRS in exercise intolerance is provided.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.026
GPT teacher head0.286
Teacher spread0.260 · 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 designNot applicable
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

Citations101
Published2000
Admission routes1
Has abstractyes

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