A Parametric Approach to Estimate Survival Time of Diabetic Nephropathy with Left Truncated and Right Censored Data
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Bibliographic record
Abstract
Diabetic Nephropathy (DN) is the deleterious effect of diabetes mellitus on renal structure, or a function caused by it. The rate of rise in, serum creatinine is observed for the progression of DN. Retrospective data is collected from 132 patients. As 60 patients form uncensored cases, remaining 72 patients are censored cases. In this paper we have developed three models. The first model is based only on uncensored cases with left truncation. The second model also includes censored data. Fisher's information matrix has been applied to find variances and asymptotic confidence interval for the estimated parameters. The method of maximum likelihood is used to estimate unknown parameters in both the models. In the last model, onset times are arranged as to estimate mean onset time of DN for all the patients by using application of order statistic. We aim to predict onset time of DN for new diabetic patients.
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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 | 0.004 |
| 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 | 0.000 | 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 it