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Record W2107318004 · doi:10.1111/jns5.12042

Progression in idiopathic, diabetic, paraproteinemic, alcoholic, and<scp>B12</scp>deficiency neuropathy

2013· article· en· W2107318004 on OpenAlexafffund
Shafina Sachedina, Cory Toth

Bibliographic record

VenueJournal of the Peripheral Nervous System · 2013
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
FundersAlberta Heritage Foundation for Medical Research
KeywordsMedicineDiabetic neuropathyDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

We determined prospectively the clinical and electrophysiological progression of idiopathic, diabetic, paraproteinemic, alcoholic, and B12 deficiency neuropathy in 606 subjects over 3 years. We hypothesized that idiopathic peripheral neuropathy would demonstrate slower progression when compared with other etiologies. Laboratory assessments were used to determine the etiology of peripheral neuropathy at baseline and after 3 years. When compared with peripheral neuropathy related to type 1 or type 2 diabetes mellitus, subjects with idiopathic peripheral neuropathy progressed much slower, but demonstrated similar rates of progression to that of the other groups. Overall, detectable progression was minimal over 3 years. After 3 years, only 3% of cases of idiopathic peripheral neuropathy had any potentially identifiable causes discovered. Clinical and electrophysiological detection of very slow progression for these five types of peripheral neuropathy is possible using currently established clinical scales and standard electrophysiological techniques.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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 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

Citations11
Published2013
Admission routes2
Has abstractyes

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