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PROGRESS IN CLINICAL NEUROSCIENCES: CHARCOT‐MARIE‐TOOTH DISEASE AND RELATED INHERITED PERIPHERAL NEUROPATHIES

2002· article· en· W2133644189 on OpenAlexaff
TJ Benstead, IA. Grant

Bibliographic record

VenueJournal of the Peripheral Nervous System · 2002
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsCanadian Journal of Communication (Canada)
Fundersnot available
KeywordsTooth diseaseDiseaseMedicinePathologicalNeuroscienceGenetic testingBioinformaticsPathologyPsychologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

The classification of Charcot‐Marie‐Tooth disease and related hereditary motor and sensory neuropathies has evolved to incorporate clinical, electrophysiological and burgeoning molecular genetic information that characterize the many disorders. For several inherited neuropathies, the gene product abnormality is known and for others, candidate genes have been identified. Genetic testing can pinpoint a specific inherited neuropathy for many patients. However, clinical and electrophysiological assessments continue to be essential tools for diagnosis and management of this disease group. This article reviews clinical, electrophysiological, pathological and molecular aspects of hereditary motor and sensory neuropathies.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.126
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.271
Teacher spread0.230 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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