Bibliographic record
Abstract
Although most investigators still define as ‘elderly’ those older than 65 years of age, recently, many would consider elderly to be those 75–80 years or older, mainly because those 65–75 years of age are still active, continue working and are relatively healthy. The care of the elderly who require chronic dialysis is more complex than the management of their younger counterparts owing to their frequent comorbid conditions, numerous impairments, functional limitations and lack of social support. The ideal timing of dialysis initiation in the elderly with slowly progressing chronic kidney disease has not been clearly defined because we have not defined predictors that may negatively affect their outcomes. Recent developments in the management of hypertension and other complications, and the addition of an appropriate diet, may delay progression to dialysis. In the absence of severe comorbidity, the choice of dialysis rather than conservative nondialysis therapy is associated with longer survival in elderly patients but not in those with multiple comorbidities. Quality of life and survival rates seem to be similar in elderly patients on either hemodialysis or peritoneal dialysis, although selection bias may confound these findings. Assisted peritoneal dialysis is a suitable method for frail elderly patients who choose to be dialyzed at home.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".