Introduction and context: the past, present and future of CKD research
Bibliographic record
Abstract
Chronic kidney disease (CKD) and its progression to the need for renal replacement therapy (RRT) are important causes of distress for patients and their families, but also a very important economic and logistic burden for society. Even more importantly, a great majority of CKD patients die due to cardiovascular disease (CVD) before reaching the need for RRT. Thus, nephrologists should focus their efforts not only on preventing or at least delaying CKD progression, but also in reducing the risk of CVD. Unfortunately, CKD is not a homogeneous disease and its progression varies considerably, even among patients with the same underlying disease and the same level of renal function, making its therapeutic approach more and more complicated. This complexity in outcomes has led to vigorous efforts of groups of outstanding nephrologists and their collaborators working within the realm of basic science, clinical research and knowledge translation. The high impact that CKD and its complications have on organizational and economic systems has prompted enquiry into all aspects of care delivery from screening to multidisciplinary care.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".