DIAGNOSTIC TEST OF TORONTO AND MODIFIED TORONTO SCORING, MONOFILAMENT TEST, AND VIBRATE SENSATION TEST USING 128 HZ TUNING FORK FOR DIABETIC POLINEUROPATHY
Bibliographic record
Abstract
Background. The prevalence of diabetes mellitus has been epidemically increasing throughout all the world population, and diabetic polyneuropathy (PNP-DM) is one of the most common neurologic manifestation of this disease. Clinical research has proved that effective bedside screening of PNP-DM can significantly reduce the incidence of foot ulcer and limb amputation. Objective. To measure the diagnostic test of polyneuropathy scoring, monofilament 10-g SemmesWeinstein test, and 128 Hz tuning fork test as an early detection measure for PNP-DM.Methods. This research was conducted using a cross sectional approach from Januari 2016 to Juli 2017.Results. Among the total study population of 43 (23 men and 20 woman), Modified Toronto Score has the highest sensitivity (100%), PPV (93%) and accuracy (93%). Toronto score has the highest NPV (9%).Conclusion. Modified Toronto Score has good diagnostic value as screening tool in PNP-DM.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".