MétaCan
Menu
Back to cohort
Record W2415793995

[Sporadic inclusion body myositis and amyloid].

2014· article· en· W2415793995 on OpenAlexaff
Masashi Aoki, Naoki Suzuki

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsCentre for Movement Disorders
Fundersnot available
KeywordsMedicineEtiologyMuscle biopsyAtrophyInclusion body myositisPathologyPolymyositisMuscle weaknessWeaknessAmyloid (mycology)InflammationMuscle atrophyMyositisAmyloidosisBiopsyInternal medicineAnatomy
DOInot available

Abstract

fetched live from OpenAlex

Sporadic inclusion body myositis (sIBM) is an intractable and progressive skeletal muscle disease of unknown etiology and without effective treatment. While the etiology is still unknown, however, genetic factors, aging, life style, and environmental factors may be involved. Muscle biopsy typically reveals endomysial inflammation, invasion of mononuclear cells into non-necrotic fibers and rimmed vacuoles, suggesting inflammation and degeneration co-exist as part of the pathomechanism. Recent studies implicate amyloid beta accumulation, defects of proteolysis, and immune system abnormalities. The clinical course is slow with chronic worsening. Diagnosis of sIBM is usually made 5 years after onset. Muscle weakness and atrophy in the quadriceps, wrist flexor and finger flexors are the typical neurological findings of sIBM. Dysphagia and asymmetric weakness are often found. Serum creatine kinase is usually below 2,000 IU/L. sIBM is generally refractory to current therapy, such as steroids or immunosuppressants. Elucidation of the pathomechanism of sIBM is the most important to therapy.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.007

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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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 designCase report
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicInflammatory Myopathies and DermatomyositisFrench-language works237,207