International quotidian dialysis registry: Annual report 2009
Bibliographic record
Abstract
The International Quotidian Dialysis Registry (IQDR) is a global initiative designed to study practices and outcomes associated with the use of hemodialysis regimens of increased frequency and/or duration. Several small studies suggest that compared with conventional hemodialysis (HD), short-daily, nocturnal, and long conventional HD regimens may improve surrogate endpoints and quality of life. However, methodologically robust comparisons on hard outcomes are sorely lacking. The IQDR represents the first-ever attempt to aggregate long-term follow-up data from centers utilizing alternative HD regimens worldwide, and will have adequate statistical power to examine the effects of these regimens on multiple clinical endpoints, including mortality. To date, the IQDR has enrolled patients from Canada, the United States, Australia, and New Zealand, with plans in place to begin linking with additional commercial databases and national registries. This fifth annual report of the IQDR describes (1) a proposed governance structure that will facilitate international collaboration, stakeholder input and funding; (2) data sources and participating registries; (3) recruitment to date and patient baseline characteristics; and (4) an agenda for future research.
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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".