The Transmuted Weibull Regression Model: an Application to Type 2 Diabetes Mellitus Data
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Bibliographic record
Abstract
In this paper, we are considering the transmuted Weibull distribution to investigate the role of oxidative stress markers as indicators of risk of injury of the lower extremities in patients with type 2 diabetes mellitus. A group of patients was studied until medical discharge assessing the following variables: glycated hemoglobin and three blood markers of oxidative status. In face of explicative covariates, we are considering the regression approach of the transmuted model to fit this real dataset. The inference was considere by using the method of maximum likelihood and the consistency of the estimators were verified by a Monte Carlo simulation study presented in this manuscript. Some properties as the moment generation function, median and the behaviors of the hazard and survival functions, are also included in this study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it