A New Initiative in Nephrology: ‘Kidney Disease: Improving Global Outcomes’
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
The burden of kidney disease: Improving global outcomes. Chronic kidney disease (CKD) is a worldwide public health problem with an increasing incidence and prevalence of patients requiring replacement therapy. There is an even higher prevalence of patients in earlier stages of CKD, with adverse outcomes such as kidney failure, cardiovascular disease, and premature death. Patients at earlier stages of CKD can be detected through laboratory testing and their treatment is effective in slowing the progression to kidney failure and reducing cardiovascular events. The evidence-based care of these patients are universal and independent of their geographic location. This paper describes the need to develop a uniform and global public health approach to the worldwide epidemic of CKD. It is to this end that a new initiative Kidney Disease: Improving Global Outcomes' has been established. Some current and future activities of this initiative are described. They include among others modification of the classification of CKD, the development of guidelines on hepatitis C, the organisation of consensus conferences like on Renal Osteodystrophy, and the creation of a website allowing the comparison of the five main English language clinical practice guidelines in kidney disease worldwide.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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