Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Hypertension and diabetes are common risk factors for nephropathy as well as for neuropathy, retinopathy, cardiovascular disease, and cerebrovascular disease. Diabetic nephropathy occurs in 20% to 40% of patients with type 2 diabetes mellitus and is the single most important cause of end-stage renal disease (ESRD) worldwide, accounting for 40% to 45% of new cases in the United States. The incidence of ESRD is predicted to increase as the prevalence of type 2 diabetes mellitus and obesity continue to increase. METHODS: Clinical data from the recent classes of antihypertensive agents are reviewed in the context of hypertension reduction guidelines and prevention of diabetic nephropathy. RESULTS: Numerous clinical trials have demonstrated that angiotensin receptor blockers (ARBs) are safe and effective antihypertensive treatments that slow the progression of renal disease in people with diabetes and/or hypertension, and macroalbuminuria. CONCLUSION: The tolerable adverse event profile of ARBs and their renoprotective benefits beyond blood pressure reduction make ARBs a useful first-line treatment in people with, or at risk of developing, renal disease. As the incidence of obesity-related cardiovascular disease and renal risk factors continues to grow, future studies are required to directly assess the renoprotective effects of ARBs in overweight or obese patient subgroups. Because renin angiotensin system (RAS) inhibitors target the key mechanisms underlying these conditions, they may be particularly beneficial for the prevention of ESRD in the growing group of patients with obesity-related hypertension and the metabolic syndrome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it