The vasopressin system: new insights for patients with kidney diseases
Bibliographic record
Abstract
People with chronic kidney disease (CKD) are at risk of severe outcomes, such as end-stage renal disease or cardiovascular disease, and CKD is a globally increasing health burden with a high personal and economic cost. Despite major progresses in prevention and therapeutics in last decades, research is still needed to reverse this epidemic trend. The regulation of water balance and the state of activation of the vasopressin system have emerged as factors tightly associated with kidney health, in the general population but also in specific conditions; among them, various stages of CKD, diabetes and autosomal dominant polycystic kidney disease (ADPKD). Basic science findings and also epidemiological evidence have justified important efforts towards interventional studies supporting causality, and opening therapeutic avenues. On the basis of recent clinical data, the blockade of V2 vasopressin receptors using tolvaptan in patients with rapidly progressing ADPKD has been granted in several countries, and a long-term randomized trial evaluating the effect of an increase in water intake in patients with CKD is on-going.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".