Addressing the burden of dialysis around the world: <scp>A</scp> summary of the roundtable discussion on dialysis economics at the <scp>F</scp>irst <scp>I</scp>nternational <scp>C</scp>ongress of <scp>C</scp>hinese <scp>N</scp>ephrologists 2015
Bibliographic record
Abstract
To address the issue of heavy dialysis burden due to the rising prevalence of end-stage renal disease around the world, a roundtable discussion on the sustainability of managing dialysis burden around the world was held in Hong Kong during the First International Congress of Chinese Nephrologists in December 2015. The roundtable discussion was attended by experts from Hong Kong, China, Canada, England, Malaysia, Singapore, Taiwan and United States. Potential solutions to cope with the heavy burden on dialysis include the prevention and retardation of the progression of CKD; wider use of home-based dialysis therapy, particularly PD; promotion of kidney transplantation; and the use of renal palliative care service.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".