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Scoring systems to screen for diabetic peripheral neuropathy

2018· article· en· W4248154621 on OpenAlexaff
Zhirong Yang, Ru Chen, Yuan Zhang, Yuansheng Huang, Tianpei Hong, Feng Sun, Linong Ji, Siyan Zhan

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPeripheral neuropathyMedicinePeripheralEndocrine systemDiabetes mellitusDiabetic neuropathyInternal medicineEndocrinologyHormone

Abstract

fetched live from OpenAlex

This is a protocol for a Cochrane Review (Diagnostic test accuracy). The objectives are as follows: To determine the diagnostic accuracy of each scoring system as triage to screen for diabetic peripheral neuropathy (DPN) involving limbs within different settings, or as replacement of nerve conduction studies (NCS) for the clinical diagnosis of DPN involving limbs, with NCS as the reference standard.

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)0.025
metaresearch head score (Gemma)0.100
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.100
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0090.016
Bibliometrics0.0180.013
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.002

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 head0.078
GPT teacher head0.362
Teacher spread0.284 · 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 designSystematic review
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

Citations57
Published2018
Admission routes1
Has abstractyes

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