Bibliographic record
Abstract
In Australia, 12% of the hemodialysis population dialyze at home. Until recently, the majority of these patients dialyzed for similar hours to those in satellite dialysis. However, in the past 5 years there has been a new departure such that in many centers the concept of home hemodialysis is now synonymous with extended hours dialysis. Registry data supports the concept that increased frequency and duration of dialysis may result in improved patient survival and a reduction in cardiovascular risk profile. It is hoped, therefore, that the long recognized survival benefit observed in home hemodialysis patients may be further augmented by the swing to extended hours dialysis in this patient population. In addition to the physiological benefits of extended hours home dialysis, there are clear quality of life, social, and economic advantages associated with dialyzing at home. There are however a number of perceived disadvantages to home hemodialysis including the application and time commitment required for training, the potential for relationship strain or "burnout," and reluctance to "hospitalize" the home. Overall, however, in this new era of extended hours dialysis, the advantages both physiological and lifestyle of home hemodialysis far outweigh the disadvantages.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".