Evaluation on the Value of the Clinical Diagnosis Methods for Diabetic Peripheral Neuropathy
Bibliographic record
Abstract
Objective: To assess the efficacy of Toronto clinical scoring system(TCSS),Michigan neuropathy screening instrument(MNSI) and neuropathy symptom score/neuropathy disability score(NSS/NDS) in the diagnosis of diabetic peripheral neuropathy.Method: Using the results of the specificity,sensitivity,Youden index,value of Kappar,the ROC curve and accuracy of the examinations were analyzed.Results: TCSS or MNSI had a higher consistency with the nerve conduction velocity examination(P0.05)than NSS/NDS(P0.01).TCSS or MNSI had a higher accuracy(Az=0.829 or 0.793),but NSS/NDS had a lower accuracy(Az=0.563).NSS/NDS does not apply to clinical DPN screening and diagnosis,MNSI suitable for outpatient service inspection,TCSS suitable for hospitalized patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".