Bibliographic record
Abstract
The objectives of hemodialysis have moved from the diffusive clearance of small molecular weight uremic toxins and achieving dialyzer urea adequacy targets to emphasis on improving clinical outcomes in end stage renal failure patients by increasing larger sized uremic toxin clearance. Clinical emphasis in the last few decades has focused on increasing middle molecule weight toxin clearance by hemodiafiltration. Although long-term data is still lacking, short-term outcomes appear promising. Advancements in nanotechnology have now introduction a new generation of medium cut-off membrane dialyzers which allow diffusive clearance of similar middle molecular weight uremia toxin clearance as hemodiafiltration, without increased albumin losses. As these dialyzers have only recently been introduced into clinical practice, no long-term outcomes are available to determine the relative benefits or advantages of this approach. As dialyzers are now designed to maximize diffusive or convective clearance, or provide a combination, then clinicians can now choose dialyzers tailored to the individual patient needs depending on clinical circumstances. We review the key important features in choosing a dialyzer for patients with end stage renal failure and acute kidney injury.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".