Risk Assessment of Type-2 Diabetes Mellitus using Canadian Risk Questionnaire
Bibliographic record
Abstract
Type 2 Diabetes Mellitus (T2DM) is a disease that manifests itself gradually and over time.Diabetes detection at an early stage is critical for delaying the disease progression.The Canadian Risk (CANRISK) questionnaire, with slight modifications, was used to determine who is the most at risk of getting diabetes mellitus.Therefore, a prospective observational study has been conducted in community nearby Maharishi Markandeshwar Institute of Medical Sciences and Research (MMIMSR), Mullana (Ambala, India).A total of 200 subjects (140 males and 60 Females) were enrolled by using CANRISK (with slight modifications) which includes parameters like Body mass index (BMI), waist circumference, genetics, smoking, alcohol consumption, physical activity etc., out of which 51(25.5%), 71(35.5%)and 78(39%) were found at low, moderate and high risk, respectively.A post counselling assessment was done after promoting healthy lifestyle and enhancing awareness among them about obesity, physical activity, smoking cessation and stopping alcohol consumption.It was observed that 40.5%, 31.5% and 28% subjects were at low, moderate and high risk, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".