Nutech Functional Score: A New Functional Scoring System for Patients With Cerebrovascular Accidents
Bibliographic record
Abstract
Background: Stroke or cerebrovascular accident happens when a part of the brain gets poor supply of blood that leads to either hemorrhage or blockage due to deoxygenation. To measure stroke outcomes, various stroke scales are invented in the last few decades. The present study has compared a novel stroke scale, Nutech functional score (NFS) to that with the most widely used and globally recognized European stroke scale (ESS). Methods: NFS has been designed with 22 different parameters taking into consideration its ability to measure neurological as well as functional impairments associated with stroke. Each symptom has been assigned scores (1, 2, 3, 4, 5) that runs in direction from extreme bad (1) to normal (5). The scores are converted to numeric values using an empirical formula. We have compared both the NFS and ESS scores for measuring stroke outcomes. Results: NFS is able to assess motor, sensory and autonomic parameters for stroke patients. It assesses not only the clinical symptoms but the overall change in quality of life. ESS fails to measure all kinds of functional parameters and it involves tedious calculations. Conclusion: NFS has proven to be a much simpler and efficient scoring system in comparison with ESS which is a 14-point stroke scale. NFS is a multiple use scale which can measure more parameters than ESS and can be used universally to assess the patients suffering with stroke. J Neurol Res. 2015;5(4-5):246-251 doi: http://dx.doi.org/10.14740/jnr352w
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".