Discriminant Analysis to Predict the Hypertension in Women Aged 25–54 Years
Bibliographic record
Abstract
BACKGROUND: Hypertension is generally associated with the contributing risk factor for cardiovascular disease in adults. This research is aimed to create a prediction model of the hypertension incidence in women aged 15 through 54 years. MATERIAL & METHODS: The research subjects are 117 women whose ages range from 27 to 54 years living in the village in the central district of Bogor. Through the instrumentation and Vo2 max measuring performed, the information was gathered concerning the following aspects: a) socio-demographic status; b) the abdominal girth; c) fasting blood glucose level; d) body mass index; e) blood lipids including the total cholesterol and triglycerides. The data analysis was conducted using discriminant analysis. RESULTS: The results of multivariable discriminant analysis showed that the level of Vo2 max is the only distinction maker of the incidence of hypertension with the final equation model Zscore = -3.033 + 0.102*Vo2 max and the cut off point -0.00018. CONCLUSION: Concerted efforts from all concerned parties are needed to prevent the hypertension especially through the physical activities relevant to a more quality lifestyle.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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".